Clinical value of Alzheimer's disease biomarker testing

INTRODUCTION

In the Investigating the Impact of Alzheimer's Disease Diagnostics in British Columbia (IMPACT-AD BC) study, we aimed to understand how Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarker testing-used in medical care-impacted medical decision-making (medical utility), personal decision-making (personal utility), and health system economics.

METHODS

The study was designed as an observational, longitudinal cohort study. A total of 149 patients were enrolled between February 2019 and July 2021. Patients referred to memory clinics were approached to participate if their dementia specialist ordered AD CSF biomarker testing as part of their routine medical care, and the clinical scenario met the appropriate use criteria for lumbar puncture and AD CSF biomarker testing. For the medical utility pillar, detailed clinical management plans were collected via physician questionnaires pre- and post-biomarker disclosure.

RESULTS

Patients with completed management questionnaires (n = 142) had a median age of 64 (interquartile range: 59-69) years, 48% were female, and 60% had CSF biomarker profiles on the AD continuum. Clinical management changed in 89.4% of cases. AD biomarker testing was associated with decreased need for other diagnostic procedures, including brain imaging (-52.0%) and detailed neuropsychological assessments (-63.2%), increased referrals and counseling (57.0%), and guided AD-related drug prescriptions (+88.4% and -50.0% in biomarker-positive and -negative cases, respectively).

DISCUSSION

AD biomarker testing was associated with significant and positive changes in clinical management, including decreased health care resource use, therapy optimization, and increased patient and family member counseling. While certain changes in management were linked to the AD biomarker profile (e.g., referral to clinical trials), the majority of changes were independent of baseline clinical presentation and level of cognitive impairment, demonstrating a broad value for AD biomarker testing in individuals meeting the appropriate use criteria for testing.

Personal value of Alzheimer's disease biomarker testing and result disclosure from the patient and care partner perspective

INTRODUCTION

We described patients' and care partners' experiences with Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarker testing and result disclosure in routine care.

METHODS

IMPACT-AD BC is an observational study of clinic patients who underwent AD CSF biomarker testing as part of their routine medical care (n = 142). In the personal utility arm of the study, semi-structured phone interviews were conducted with a subset of patients (n = 34), and separately with their care partners (n = 31). Post-disclosure interviews were conducted ∼1 month and ∼6 months after biomarker result disclosure and investigated the patients' decision-making process around testing, impact of receiving results, wellness and lifestyle changes, and future planning.

RESULTS

A majority of patients (90%) rated their decision to undergo testing as "easy." Post-disclosure, the majority (82%) reported overall positive feelings from having greater certainty and the ability to plan ahead, and results spurred them to adopt/continue healthy behaviors such as exercise (84%) and cognitive activities (54%). Care partners expressed relief from having more diagnostic certainty, increased appreciation of future caregiving responsibilities, and a desire to connect with support resources.

DISCUSSION

Perspectives of persons with lived experience in dementia provide new insight into the value of biomarker testing and should be included as part of evidence-guided considerations for pre-test counseling and result disclosure. Moreover, study findings identify an interval when patients and care partners are highly receptive to positive lifestyle and medical interventions.

Chronic Diseases Associated With Mortality in British Columbia, Canada During the 2021 Western North America Extreme Heat Event

Western North America experienced an unprecedented extreme heat event (EHE) in 2021, characterized by high temperatures and reduced air quality. There were approximately 740 excess deaths during the EHE in the province of British Columbia, making it one of the deadliest weather events in Canadian history. It is important to understand who is at risk of death during EHEs so that appropriate public health interventions can be developed. This study compares 1,614 deaths from 25 June to 02 July 2021 with 6,524 deaths on the same dates from 2012 to 2020 to examine differences in the prevalence of 26 chronic diseases between the two groups. Conditional logistic regression was used to estimate the odds ratio (OR) for each chronic disease, adjusted for age, sex, and all other diseases, and conditioned on geographic area. The OR [95% confidence interval] for schizophrenia among all EHE deaths was 3.07 [2.39, 3.94], and was larger than the ORs for other conditions. Chronic kidney disease and ischemic heart disease were also significantly increased among all EHE deaths, with ORs of 1.36 [1.18, 1.56] and 1.18 [1.00, 1.38], respectively. Chronic diseases associated with EHE mortality were somewhat different for deaths attributed to extreme heat, deaths with an unknown/pending cause, and non-heat-related deaths. Schizophrenia was the only condition associated with significantly increased odds of EHE mortality in all three subgroups. These results confirm the role of mental illness in EHE risk and provide further impetus for interventions that target specific groups of high-risk individuals based on underlying chronic conditions.

Integrated Genotoxicity Testing of three anti-infective drugs using the TGx-DDI transcriptomic biomarker and high-throughput CometChip® assay in TK6 cells

Genotoxicity testing relies on the detection of gene mutations and chromosome damage and has been used in the genetic safety assessment of drugs and chemicals for decades. However, the results of standard genotoxicity tests are often difficult to interpret due to lack of mode of action information. The TGx-DDI transcriptomic biomarker provides mechanistic information on the DNA damage-inducing (DDI) capability of chemicals to aid in the interpretation of positive in vitro genotoxicity data. The CometChip^® assay was developed to assess DNA strand breaks in a higher-throughput format. We paired the TGx-DDI biomarker with the CometChip^® assay in TK6 cells to evaluate three model agents: nitrofurantoin (NIT), metronidazole (MTZ), and novobiocin (NOV). TGx-DDI was analyzed by two independent labs and technologies (nCounter^® and TempO-Seq^®). Although these anti-infective drugs are, or have been, used in human and/or veterinary medicine, the standard genotoxicity testing battery showed significant genetic safety findings. Specifically, NIT is a mutagen and causes chromosome damage, and MTZ and NOV cause chromosome damage in conventional in vitro tests. Herein, the TGx-DDI biomarker classified NIT and MTZ as non-DDI at all concentrations tested, suggesting that NIT’s mutagenic activity is bacterial specific and that the observed chromosome damage by MTZ might be a consequence of in vitro test conditions. In contrast, NOV was classified as DDI at the second highest concentration tested, which is in line with the fact that NOV is a bacterial DNA-gyrase inhibitor that also affects topoisomerase II at high concentrations. The lack of DNA damage for NIT and MTZ was confirmed by the CometChip^® results, which were negative for all three drugs except at overtly cytotoxic concentrations. This case study demonstrates the utility of combining the TGx-DDI biomarker and CometChip^® to resolve conflicting genotoxicity data and provides further validation to support the reproducibility of the biomarker.

Efficacy of washing produce in removing human coronavirus OC43 and murine norovirus

AIMS

Fresh produce is often a vehicle for the transmission of foodborne pathogens such as human norovirus. Thus, it is recommended to wash the surface of produce before consumption, and one of the most common ways to wash produce is by rinsing under running tap water. This study determined the effectiveness of removal of human coronavirus-OC43 (HCoV-OC43), as a surrogate for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and murine norovirus-1 (MNV-1), as a surrogate for human norovirus, from contaminated lettuce, apples and cucumbers.

METHODS AND RESULTS

The produce surfaces were artificially inoculated in conjunction with faecal material to represent natural contamination. Rinsing under tap water for 10 s at 40 ml/s removed 1.94 ± 0.44, 1.42 ± 0.00 and 1.42 ± 0.42 log of HCoV-OC43 from apple, cucumber and lettuce respectively. The same washing technique removed 1.77 ± 0.17, 1.42 ± 0.07 and 1.79 ± 0.14 log of MNV-1 from apple, cucumber and lettuce respectively. This washing technique was effective at reducing a significant amount of viral contamination, however, it was not enough to eliminate the entire contamination. There was no significant difference in the reduction of viral load between the two viruses, nor between the three surfaces tested in this study.

CONCLUSIONS

Our data suggest that washing under tap water would be an efficient way of reducing the risk of foodborne viral transmission only if the level of contamination is less than 2 log PFU.

SIGNIFICANCE AND IMPACT OF STUDY

This study demonstrates that running tap water was effective at reducing the amount of infectious HCoV-OC43 and MNV on produce surfaces, and washing produce continues to be an important task to perform prior to consumption to avoid infection by foodborne viruses, particularly for foods which are eaten raw.

Modulation of type 1 cannabinoid receptor activity by cannabinoid by-products from Cannabis sativa and non-cannabis phytomolecules

Cannabis sativa contains more than 120 cannabinoids and 400 terpene compounds (i.e., phytomolecules) present in varying amounts. Cannabis is increasingly available for legal medicinal and non-medicinal use globally, and with increased access comes the need for a more comprehensive understanding of the pharmacology of phytomolecules. The main transducer of the intoxicating effects of Cannabis is the type 1 cannabinoid receptor (CB1R). ∆⁹-tetrahydrocannabinolic acid (∆⁹-THCa) is often the most abundant cannabinoid present in many cultivars of Cannabis. Decarboxylation converts ∆⁹-THCa to ∆⁹-THC, which is a CB1R partial agonist. Understanding the complex interplay of phytomolecules—often referred to as “the entourage effect”—has become a recent and major line of inquiry in cannabinoid research. Additionally, this interest is extending to other non-Cannabis phytomolecules, as the diversity of available Cannabis products grows. Here, we chose to focus on whether 10 phytomolecules (∆⁸-THC, ∆^6a,10a-THC, 11-OH-∆⁹-THC, cannabinol, curcumin, epigallocatechin gallate, olivetol, palmitoylethanolamide, piperine, and quercetin) alter CB1R-dependent signaling with or without a co-treatment of ∆⁹-THC. Phytomolecules were screened for their binding to CB1R, inhibition of forskolin-stimulated cAMP accumulation, and βarrestin2 recruitment in Chinese hamster ovary cells stably expressing human CB1R. Select compounds were assessed further for cataleptic, hypothermic, and anti-nociceptive effects on male mice. Our data revealed partial agonist activity for the cannabinoids tested, as well as modulation of ∆⁹-THC-dependent binding and signaling properties of phytomolecules in vitro and in vivo. These data represent a first step in understanding the complex pharmacology of Cannabis- and non-Cannabis-derived phytomolecules at CB1R and determining whether these interactions may affect the physiological outcomes, adverse effects, and abuse liabilities associated with the use of these compounds.

Chronic Embryo-Larval Exposure of Fathead Minnows to the Pharmaceutical Drug Metformin: Survival, Growth, and Microbiome Responses

Metformin is a glucose-lowering drug commonly found in municipal wastewater effluents (MWWEs). The present study investigated the chronic effects of metformin in early-life stages of the fathead minnow (Pimephales promelas). Endpoints assessed were growth, survival, and deformities. The larval gut microbiome was also examined using 16 S ribosomal RNA gene amplicon sequencing to determine microbial community composition and alpha and beta diversity. Eggs and larvae were exposed to metformin measured concentrations (mean [standard deviation]) of 0.020 (0.017) μg/L (for controls) and 3.44 (0.23), 33.6 (1.6), and 269 (11) μg/L in a daily static-renewal setup, with 20 embryos per beaker. The low and middle metformin exposure concentrations represent river and MWWE concentrations of metformin. To detect small changes in growth, we used 18 replicate beakers for controls and 9 replicates for each metformin treatment. Over the 21-d exposure (5 d as embryos and 16 d posthatch [dph]), metformin did not affect survival or growth of larval fish. Hatch success, time to hatch, deformities in hatched fry, and survival were similar across all treatments. Growth (wet wt, length, and condition factor) assessed at 9 and 16 dph was also unaffected by metformin. Assessment of the microbiome showed that the larvae microbiome was dominant in Proteobacteria and Firmicutes, with small increases in Proteobacteria and decreases in Firmicutes with increasing exposure to metformin. No treatment effects were found for microbiome diversity measures. Control fish euthanized with the anesthetic tricaine methane sulfonate had decreased alpha diversity compared to those sampled by spinal severance. This experiment demonstrates that metformin at environmentally relevant concentrations (3.44 and 33.6 μg/L) and at 10 times MWWE concentrations (269 µg/L) does not adversely affect larval growth or gut microbiome in this ubiquitous freshwater fish species. Environ Toxicol Chem 2022;41:635-647. © 2021 Her Majesty the Queen in Right of Canada. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. Reproduced with the permission of the Minister of Environment and Climate Change Canada.

Data-driven staging of genetic frontotemporal dementia using multi-modal MRI

Frontotemporal dementia in genetic forms is highly heterogeneous and begins many years to prior symptom onset, complicating disease understanding and treatment development. Unifying methods to stage the disease during both the presymptomatic and symptomatic phases are needed for the development of clinical trials outcomes. Here we used the contrastive trajectory inference (cTI), an unsupervised machine learning algorithm that analyzes temporal patterns in high‐dimensional large‐scale population datasets to obtain individual scores of disease stage. We used cross‐sectional MRI data (gray matter density, T1/T2 ratio as a proxy for myelin content, resting‐state functional amplitude, gray matter fractional anisotropy, and mean diffusivity) from 383 gene carriers (269 presymptomatic and 115 symptomatic) and a control group of 253 noncarriers in the Genetic Frontotemporal Dementia Initiative. We compared the cTI‐obtained disease scores to the estimated years to onset (age—mean age of onset in relatives), clinical, and neuropsychological test scores. The cTI based disease scores were correlated with all clinical and neuropsychological tests (measuring behavioral symptoms, attention, memory, language, and executive functions), with the highest contribution coming from mean diffusivity. Mean cTI scores were higher in the presymptomatic carriers than controls, indicating that the method may capture subtle pre‐dementia cerebral changes, although this change was not replicated in a subset of subjects with complete data. This study provides a proof of concept that cTI can identify data‐driven disease stages in a heterogeneous sample combining different mutations and disease stages of genetic FTD using only MRI metrics.