Alzheimer's disease biomarkers in Black and non-Hispanic White cohorts: A contextualized review of the evidence

Black Americans are disproportionately affected by dementia. To expand our understanding of mechanisms of this disparity, we look to Alzheimer's disease (AD) biomarkers. In this review, we summarize current data, comparing the few studies presenting these findings. Further, we contextualize the data using two influential frameworks: the National Institute on Aging–Alzheimer's Association (NIA-AA) Research Framework and NIA's Health Disparities Research Framework. The NIA-AA Research Framework provides a biological definition of AD that can be measured in vivo. However, current cut-points for determining pathological versus non-pathological status were developed using predominantly White cohorts—a serious limitation. The NIA's Health Disparities Research Framework is used to contextualize findings from studies identifying racial differences in biomarker levels, because studying biomakers in isolation cannot explain or reduce inequities. We offer recommendations to expand study beyond initial reports of racial differences. Specifically, life course experiences associated with racialization and commonly used study enrollment practices may better account for observations than exclusively biological explanations

Biomarker clusters are differentially associated with longitudinal cognitive decline in late midlife

The ability to detect preclinical Alzheimer’s disease is of great importance, as this stage of the Alzheimer’s continuum is believed to provide a key window for intervention and prevention. As Alzheimer’s disease is characterized by multiple pathological changes, a biomarker panel reflecting co-occurring pathology will likely be most useful for early detection. Towards this end, 175 late middle-aged participants (mean age 55.9 ± 5.7 years at first cognitive assessment, 70% female) were recruited from two longitudinally followed cohorts to undergo magnetic resonance imaging and lumbar puncture. Cluster analysis was used to group individuals based on biomarkers of amyloid pathology (cerebrospinal fluid amyloid-β42/amyloid-β40 assay levels), magnetic resonance imaging-derived measures of neurodegeneration/atrophy (cerebrospinal fluid-to-brain volume ratio, and hippocampal volume), neurofibrillary tangles (cerebrospinal fluid phosphorylated tau181 assay levels), and a brain-based marker of vascular risk (total white matter hyperintensity lesion volume). Four biomarker clusters emerged consistent with preclinical features of (i) Alzheimer’s disease; (ii) mixed Alzheimer’s disease and vascular aetiology; (iii) suspected non-Alzheimer’s disease aetiology; and (iv) healthy ageing. Cognitive decline was then analysed between clusters using longitudinal assessments of episodic memory, semantic memory, executive function, and global cognitive function with linear mixed effects modelling. Cluster 1 exhibited a higher intercept and greater rates of decline on tests of episodic memory. Cluster 2 had a lower intercept on a test of semantic memory and both Cluster 2 and Cluster 3 had steeper rates of decline on a test of global cognition. Additional analyses on Cluster 3, which had the smallest hippocampal volume, suggest that its biomarker profile is more likely due to hippocampal vulnerability and not to detectable specific volume loss exceeding the rate of normal ageing. Our results demonstrate that pathology, as indicated by biomarkers, in a preclinical timeframe is related to patterns of longitudinal cognitive decline. Such biomarker patterns may be useful for identifying at-risk populations to recruit for clinical trials

Measurement batch differences and between-batch conversion of Alzheimer's disease cerebrospinal fluid biomarker values

Introduction: Batch differences in cerebrospinal fluid (CSF) biomarker measurement can introduce bias into analyses for Alzheimer's disease studies. We evaluated and adjusted for batch differences using statistical methods. Methods: A total of 792 CSF samples from 528 participants were assayed in three batches for 12 biomarkers and 3 biomarker ratios. Batch differences were assessed using Bland-Altman plot, paired t test, Pitman-Morgan test, and linear regression. Generalized linear models were applied to convert CSF values between batches. Results: We found statistically significant batch differences for all biomarkers and ratios, except that neurofilament light was comparable between batches 1 and 2. The conversion models generally had high R2 except for converting P-tau between batches 1 and 3. Discussion: Between-batch conversion allows harmonized CSF values to be used in the same analysis. Such method may be applied to adjust for other sources of variability in measuring CSF or other types of biomarkers

Insulin Resistance is Associated with Increased Levels of Cerebrospinal Fluid Biomarkers of Alzheimer's Disease and Reduced Memory Function in At-Risk Healthy Middle-Aged Adults

BACKGROUND: Type 2 diabetes is associated with an increased risk for Alzheimer’s disease (AD). Regulation of normal insulin function may be important in reducing the prevalence of dementia due to AD, particularly in individuals who harbor genetic risk for or have a parental family history of AD. The relationship between insulin resistance (IR) and AD pathology remains poorly understood, particularly in midlife prior to the onset of clinical metabolic disease or cognitive decline. // OBJECTIVE: We examined associations between IR as indexed by HOMA-IR, cerebrospinal fluid (CSF) biomarkers of AD pathology, and memory in middle-aged adults enriched for AD. We postulated that higher HOMA-IR and APOE ɛ4 carriage would be associated with greater CSF AD pathology and poor memory performance. // METHODS: Cognitively asymptomatic middle-aged adults (N = 70, mean age = 57.7 years) from the Wisconsin Alzheimer’s Disease Research Center with a parental family history of dementia due to AD underwent lumbar puncture, blood draw, and neuropsychological testing. CSF AD biomarkers including soluble amyloid-β protein precursor β (sAβPPβ), amyloid-β42 (Aβ42), and phosphorylated tau (P-tau181) were examined with respect to HOMA-IR and APOE ɛ4 status. Delayed memory performance was examined with respect to HOMA-IR, CSF AD biomarkers, and APOE ɛ4 status. // RESULTS: Higher HOMA-IR was associated with higher sAβPPβ and Aβ42 . APOE ɛ4 carriers had significantly higher levels of sAβPPα, sAβPPβ, and P-tau181/Aβ42 compared to noncarriers. The concurrent presence of higher HOMA-IR and CSF AD pathology predicted worse delayed memory performance. // CONCLUSION: Overall, the findings suggest that IR and APOE ɛ4 are contributing factors to the development of AD pathology in midlife, and provide support for targeting insulin function as a potentially modifiable risk factor for AD

An Administrative Claims Model for Profiling Hospital 30-Day Mortality Rates for Pneumonia Patients

Outcome measures for patients hospitalized with pneumonia may complement process measures in characterizing quality of care. We sought to develop and validate a hierarchical regression model using Medicare claims data that produces hospital-level, risk-standardized 30-day mortality rates useful for public reporting for patients hospitalized with pneumonia.Retrospective study of fee-for-service Medicare beneficiaries age 66 years and older with a principal discharge diagnosis of pneumonia. Candidate risk-adjustment variables included patient demographics, administrative diagnosis codes from the index hospitalization, and all inpatient and outpatient encounters from the year before admission. The model derivation cohort included 224,608 pneumonia cases admitted to 4,664 hospitals in 2000, and validation cohorts included cases from each of years 1998-2003. We compared model-derived state-level standardized mortality estimates with medical record-derived state-level standardized mortality estimates using data from the Medicare National Pneumonia Project on 50,858 patients hospitalized from 1998-2001. The final model included 31 variables and had an area under the Receiver Operating Characteristic curve of 0.72. In each administrative claims validation cohort, model fit was similar to the derivation cohort. The distribution of standardized mortality rates among hospitals ranged from 13.0% to 23.7%, with 25(th), 50(th), and 75(th) percentiles of 16.5%, 17.4%, and 18.3%, respectively. Comparing model-derived risk-standardized state mortality rates with medical record-derived estimates, the correlation coefficient was 0.86 (Standard Error = 0.032).An administrative claims-based model for profiling hospitals for pneumonia mortality performs consistently over several years and produces hospital estimates close to those using a medical record model

Gene-Expression Signatures Can Distinguish Gastric Cancer Grades and Stages

Microarray gene-expression data of 54 paired gastric cancer and adjacent noncancerous gastric tissues were analyzed, with the aim to establish gene signatures for cancer grades (well-, moderately-, poorly- or un-differentiated) and stages (I, II, III and IV), which have been determined by pathologists. Our statistical analysis led to the identification of a number of gene combinations whose expression patterns serve well as signatures of different grades and different stages of gastric cancer. A 19-gene signature was found to have discerning power between high- and low-grade gastric cancers in general, with overall classification accuracy at 79.6%. An expanded 198-gene panel allows the stratification of cancers into four grades and control, giving rise to an overall classification agreement of 74.2% between each grade designated by the pathologists and our prediction. Two signatures for cancer staging, consisting of 10 genes and 9 genes, respectively, provide high classification accuracies at 90.0% and 84.0%, among early-, advanced-stage cancer and control. Functional and pathway analyses on these signature genes reveal the significant relevance of the derived signatures to cancer grades and progression. To the best of our knowledge, this represents the first study on identification of genes whose expression patterns can serve as markers for cancer grades and stages

Cerebrospinal Fluid Markers of Alzheimer's Disease Pathology and Microglial Activation are Associated with Altered White Matter Microstructure in Asymptomatic Adults at Risk for Alzheimer's Disease

Background: The immune response in Alzheimer’s disease (AD) involves activation of microglia which may remove amyloid-β (Aβ). However, overproduction of inflammatory compounds may exacerbate neural damage in AD. AD pathology accumulates years before diagnosis, yet the extent to which neuroinflammation is involved in the earliest disease stages is unknown. Objective: To determine whether neuroinflammation exacerbates neural damage in preclinical AD. Methods: We utilized cerebrospinal fluid (CSF) and magnetic resonance imaging collected in 192 asymptomatic late-middle-aged adults (mean age = 60.98 years). Neuroinflammatory markers chitinase-3-like protein 1 (YKL-40) and monocyte chemoattractant protein-1 (MCP-1) in CSF were utilized as markers of neuroinflammation. Neural cell damage was assessed using CSF neurofilament light chain protein (NFL), CSF total tau (T-Tau), and neural microstructure assessed with diffusion tensor imaging (DTI). With regard to AD pathology, CSF Aβ42 and tau phosphorylated at threonine 181 (P-Tau181) were used as markers of amyloid and tau pathology, respectively. We hypothesized that higher YKL-40 and MCP-1 in the presence of AD pathology would be associated with higher NFL, T-Tau, and altered microstructure on DTI. Results: Neuroinflammation was associated with markers of neural damage. Higher CSF YKL-40 was associated with both higher CSF NFL and T-Tau. Inflammation interacted with AD pathology, such that greater MCP-1 and lower Aβ42 was associated with altered microstructure in bilateral frontal and right temporal lobe and that greater MCP-1 and greater P-Tau181 was associated with altered microstructure in precuneus. Conclusion: Inflammation may play a role in neural damage in preclinical AD

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Osteoclasts Are Active in Bone Forming Metastases of Prostate Cancer Patients

BACKGROUND: Bone forming metastases are a common and disabling consequence of prostate cancer (CaP). The potential role of osteoclast activity in CaP bone metastases is not completely explained. In this study, we investigated ex vivo whether the osteolytic activity is present and how it is ruled in CaP patients with bone forming metastases. METHODOLOGY: Forty-six patients affected by newly diagnosed CaP and healthy controls were enrolled. At diagnosis, 37 patients had a primary tumour only, while 9 had primary tumour and concomitant bone forming metastases. In all patients there was no evidence of metastasis to other non-bone sites. For all patients and controls we collected blood and urinary samples. We evaluated patients' bone homeostasis; we made peripheral blood mononuclear cell (PBMC) cultures to detect in vitro osteoclastogenesis; we dosed serum expression of molecules involved in cancer induced osteoclatogenesis, such as RANKL, OPG, TNF-alpha, DKK-1 and IL-7. By Real-Time PCR, we quantified DKK-1 and IL-7 gene expression on micro-dissected tumour and healthy tissue sections. PRINCIPAL FINDINGS: CaP bone metastatic patients showed bone metabolism disruption with increased bone resorption and formation compared to non-bone metastatic patients and healthy controls. The CaP PBMC cultures showed an enhanced osteoclastogenesis in bone metastatic patients, due to an increase of RANKL/OPG ratio. We detected increased DKK-1 serum levels and tissue gene expression in patients compared to controls. IL-7 resulted high in patients' sera, but its tissue gene expression was comparable in patients and controls. CONCLUSIONS: We demonstrated ex vivo that osteoclastogenesis is an active mechanism in tumour nesting of bone forming metastatic cancer and that serum DKK-1 levels are increased in CaP patients, suggesting to deeply investigate its role as tumour marker

Chimpanzee Malaria Parasites Related to Plasmodium ovale in Africa

Since the 1970's, the diversity of Plasmodium parasites in African great apes has been neglected. Surprisingly, P. reichenowi, a chimpanzee parasite, is the only such parasite to have been molecularly characterized. This parasite is closely phylogenetically related to P. falciparum, the principal cause of the greatest malaria burden in humans. Studies of malaria parasites from anthropoid primates may provide relevant phylogenetic information, improving our understanding of the origin and evolutionary history of human malaria species. In this study, we screened 130 DNA samples from chimpanzees (Pan troglodytes) and gorillas (Gorilla gorilla) from Cameroon for Plasmodium infection, using cytochrome b molecular tools. Two chimpanzees from the subspecies Pan t. troglodytes presented single infections with Plasmodium strains molecularly related to the human malaria parasite P. ovale. These chimpanzee parasites and 13 human strains of P. ovale originated from a various sites in Africa and Asia were characterized using cytochrome b and cytochrome c oxidase 1 mitochondrial partial genes and nuclear ldh partial gene. Consistent with previous findings, two genetically distinct types of P. ovale, classical and variant, were observed in the human population from a variety of geographical locations. One chimpanzee Plasmodium strain was genetically identical, on all three markers tested, to variant P. ovale type. The other chimpanzee Plasmodium strain was different from P. ovale strains isolated from humans. This study provides the first evidence of possibility of natural cross-species exchange of P. ovale between humans and chimpanzees of the subspecies Pan t. troglodytes