Introduction
The biological pathways involved in the preclinical stage of the Alzheimer's continuum are not well understood.
Methods
We used NeuroToolKit and Elecsys® immunoassays to measure ...cerebrospinal fluid (CSF) amyloid‐β (Aβ)42, Aβ40, phosphorylated tau (p‐tau), total tau (t‐tau), neurofilament light (NfL), neurogranin, sTREM2, YKL40, GFAP, IL6, S100, and α‐synuclein in cognitively unimpaired participants of the ALFA+ study, many within the Alzheimer's continuum.
Results
CSF t‐tau, p‐tau, and neurogranin increase throughout aging only in Aβ‐positive individuals, whereas NfL and glial biomarkers increase with aging regardless of Aβ status. We modelled biomarker changes as a function of CSF Aβ42/40, p‐tau and p‐tau/Aβ42 as proxies of disease progression. The first change observed in the Alzheimer's continuum was a decrease in the CSF Aβ42/40 ratio. This is followed by a steep increase in CSF p‐tau; t‐tau; neurogranin; and, to a lesser extent, in NfL and glial biomarkers.
Discussion
Multiple biological pathways are altered and could be targeted very early in the Alzheimer's continuum.
Accurate detection of characteristic proteins secreted by colon cancer tumor cells in biological fluids could serve as a biomarker for the disease. The aim of the present study was to identify and ...validate new serum biomarkers and demonstrate their potential usefulness for early diagnosis of colon cancer.
The study was organized in three sequential phases: 1) biomarker discovery, 2) technical and biological validation, and 3) proof of concept to test the potential clinical use of selected biomarkers. A prioritized subset of the differentially-expressed genes between tissue types (50 colon mucosa from cancer-free individuals and 100 normal-tumor pairs from colon cancer patients) was validated and further tested in a series of serum samples from 80 colon cancer cases, 23 patients with adenoma and 77 cancer-free controls.
In the discovery phase, 505 unique candidate biomarkers were identified, with highly significant results and high capacity to discriminate between the different tissue types. After a subsequent prioritization, all tested genes (N = 23) were successfully validated in tissue, and one of them, COL10A1, showed relevant differences in serum protein levels between controls, patients with adenoma (p = 0.0083) and colon cancer cases (p = 3.2e-6).
We present a sequential process for the identification and further validation of biomarkers for early detection of colon cancer that identifies COL10A1 protein levels in serum as a potential diagnostic candidate to detect both adenoma lesions and tumor.
The use of a cheap serum test for colon cancer screening should improve its participation rates and contribute to decrease the burden of this disease.
Due to the progressive aging of the population, Alzheimer's disease (AD) is becoming a healthcare burden of epidemic proportions for which there is currently no cure. Disappointing results from ...clinical trials performed in mild-moderate AD dementia combined with clear epidemiological evidence on AD risk factors are contributing to the development of primary prevention initiatives. In addition, the characterization of the long asymptomatic stage of AD is allowing the development of intervention studies and secondary prevention programmes on asymptomatic at-risk individuals, before substantial irreversible neuronal dysfunction and loss have occurred, an approach that emerges as highly relevant.In this manuscript, we review current strategies for AD prevention, from primary prevention strategies based on identifying risk factors and risk reduction, to secondary prevention initiatives based on the early detection of the pathophysiological hallmarks and intervention at the preclinical stage of the disease. Firstly, we summarize the evidence on several AD risk factors, which are the rationale for the establishment of primary prevention programmes as well as revising current primary prevention strategies. Secondly, we review the development of public-private partnerships for disease prevention that aim to characterize the AD continuum as well as serving as platforms for secondary prevention trials. Finally, we summarize currently ongoing clinical trials recruiting participants with preclinical AD or a higher risk for the onset of AD-related cognitive impairment.The growing body of research on the risk factors for AD and its preclinical stage is favouring the development of AD prevention programmes that, by delaying the onset of Alzheimer's dementia for only a few years, would have a huge impact on public health.
Although exposure to natural outdoor environments has been consistently associated with improved perceived general health, available evidence on a protective association between this exposure and ...specific mental health disorders such as depression and anxiety is still limited.
The aim of this study was to evaluate the effects of long-term exposure to residential green and blue spaces on anxiety and depression and intake of related medication. Additionally, we aimed to explore potential mediators and effect modifiers of this association.
The study was based on an existing adult cohort (ALFA – Alzheimer and Families) and includes 958 adult participants from Barcelona recruited in 2013–2014. For each participant residential green and blue exposure indicators surrounding greenness (NDVI), amount of green (land-cover) and access to major green spaces and blue spaces were generated for different buffers (100m, 300m and 500m). Participants reported their history of doctor-diagnosed anxiety and depressive disorders and intake of related medication. Logistic regression models were applied to assess the corresponding associations.
Increasing surrounding greenness was associated with reduced odds of self-reported history of benzodiazepines e.g. Odds ratio - OR (95%CI) = 0.62 (0.43, 0.89) for 1-interquartile range (IQR) increase in NDVI in a 300m buffer and access to major green spaces was associated with self-reported history of depression OR (95%CI) = 0.18 (0.06, 0.58). No statistically significant associations were observed with blue spaces. Air pollution (between 0.8% and 29.6%) and noise (between 2.2% and 5.3%) mediated a proportion of the associations observed, whereas physical activity and social support played a minor role.
Our findings suggest a potential protective role of green spaces on mental health (depression and anxiety) in adults, but further studies, especially longitudinal studies, are needed to provide further evidence of these benefits and of the mediation role of exposures like air pollution and noise.
•Increasing surrounding greenness associated with reduced odds of use of benzodiazepines.•Access to major green spaces was associated with self-reported history of depression.•Air pollution and noise explained a proportion of the associations observed.•No associations between blue spaces and mental health outcomes were observed.•The present study suggests a potential protective role of green spaces on mental health.
•Consistent evidence has linked air pollution and Alzheimer’s disease (AD).•We examined the association between air pollutants and AD biomarkers.•Air pollution was adversely associated with brain Aβ ...deposition and NfL biomarkers.•Most associations were driven by individuals that were Aβ-positive.•Our findings support air pollution as a modifiable environmental risk factor for AD.
Air quality contributes to incidence of Alzheimer’s disease (AD) although the underlying neurobiological mechanisms are unclear. This study was aimed to examine the association between air pollution and concentrations of cerebrospinal fluid (CSF) AD biomarkers and amyloid-β (Aβ) deposition.
Participants and methods
The sample included 156 cognitively unimpaired adults aged 57 years (61 at biomarkers assessment) with increased risk of AD from the ALFA + Study. We examined CSF levels of Aβ42, Aβ40, p-Tau, t-Tau, neurofilament light (NfL) and cerebral amyloid load (Centiloid). A Land Use Regression model from 2009 was used to estimate residential exposure to air pollutants including nitrogen dioxide (NO2,) and particulate matter (PM2.5, PM2.5 abs, PM10). This model was considered a surrogate of long-term exposure until time of data collection in 2013–2014. Participants have resided in the same residence for at least the previous 3 years. Multiple linear regression models were used to estimate associations between air pollutants and biomarkers. The effect modification by CSF Aβ status and APOE-ε4 carriership was also assessed.
A consistent pattern of results indicated that greater exposure to NO2 and PM2.5 absorbance was associated with higher levels of brain Aβ deposition, while greater exposure to PM10 and PM2.5was associated with higher levels of CSF NfL. Most associations were driven by individuals that were Aβ-positive. Although APOE-ε4 status did not significantly modify these associations, the effect of air pollutants exposure on CSF NfL levels was stronger in APOE-ε4 carriers.
In a population of cognitively unimpaired adults with increased risk of AD, long-term exposure to air pollution was associated with higher levels in biomarkers of AD pathology. While further research is granted to elucidate the mechanisms involved in such associations, our results reinforce the role of air pollution as an environmental risk factor for AD.
•Urban environmental exposures were evaluated in individuals living in Barcelona.•Urban environmental exposures were not associated with cognitive performance.•Air pollution impacts cortical ...thickness of brain regions related to AD vulnerability.•Results suggest a link between environmental exposures and cerebral vulnerability to AD.
Air quality might contribute to incidence of dementia-related disorders, including Alzheimer’s dementia (AD). The aim of our study is to evaluate the effect of urban environmental exposures (including exposure to air pollution, noise and green space) on cognitive performance and brain structure of cognitively unimpaired individuals at risk for AD.
The ALFA (ALzheimer and FAmilies) study is a prospective cohort of middle-age, cognitively unimpaired subjects, many of them offspring of AD patients. Cognitive performance was measured by the administration of episodic memory and executive function tests (N = 958). Structural brain imaging was performed in a subsample of participants to obtain morphological information of brain areas, specially focused on cortical thickness, known to be affected by AD (N = 228). Land Use Regression models were used to estimate residential exposure to air pollutants. The daily average noise level at the street nearest to each participant's residential address was obtained from noise maps. For each participant residential green exposure indicators, such as surrounding greenness or amount of green, were generated. General linear models were conducted to assess the association between environmental exposures, cognitive performance and brain structure in a cross-sectional analysis.
No significant associations were observed between urban environmental exposures and the cognitive composite (p > 0.1). Higher exposure to air pollutants, but not noise, was associated with lower cortical thickness in brain regions known to be affected by AD, especially NO2 (β = −16.4; p = 0.05) and PM10 (β = −5.34; p = 0.05). On the other hand, increasing greenness indicators was associated with greater thickness in these same areas (β = 0.08; p = 0.03).
In cognitively unimpaired adults with increased risk for AD, increased exposure to air pollution was suggested to be associated with greater global atrophy and reduced volume and thickness in specific brain areas known to be affected in AD, thus suggesting a potential link between environmental exposures and cerebral vulnerability to AD. Although more research in the field is needed, air pollution reduction is crucial for decreasing the burden of age-related disorders.
The traditional staging system is inadequate to identify those patients with stage II colorectal cancer (CRC) at high risk of recurrence or with stage III CRC at low risk. A number of gene expression ...signatures to predict CRC prognosis have been proposed, but none is routinely used in the clinic. The aim of this work was to assess the prediction ability and potential clinical usefulness of these signatures in a series of independent datasets.
A literature review identified 31 gene expression signatures that used gene expression data to predict prognosis in CRC tissue. The search was based on the PubMed database and was restricted to papers published from January 2004 to December 2011. Eleven CRC gene expression datasets with outcome information were identified and downloaded from public repositories. Random Forest classifier was used to build predictors from the gene lists. Matthews correlation coefficient was chosen as a measure of classification accuracy and its associated p-value was used to assess association with prognosis. For clinical usefulness evaluation, positive and negative post-tests probabilities were computed in stage II and III samples.
Five gene signatures showed significant association with prognosis and provided reasonable prediction accuracy in their own training datasets. Nevertheless, all signatures showed low reproducibility in independent data. Stratified analyses by stage or microsatellite instability status showed significant association but limited discrimination ability, especially in stage II tumors. From a clinical perspective, the most predictive signatures showed a minor but significant improvement over the classical staging system.
The published signatures show low prediction accuracy but moderate clinical usefulness. Although gene expression data may inform prognosis, better strategies for signature validation are needed to encourage their widespread use in the clinic.
CA125 is the best available yet insufficiently sensitive biomarker for early detection of ovarian cancer. There is a need to identify novel biomarkers, which individually or in combination with CA125 ...can achieve adequate sensitivity and specificity for the detection of earlier-stage ovarian cancer.
In the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we measured serum levels of 92 preselected proteins for 91 women who had blood sampled ≤18 months prior to ovarian cancer diagnosis, and 182 matched controls. We evaluated the discriminatory performance of the proteins as potential early diagnostic biomarkers of ovarian cancer.
Nine of the 92 markers; CA125, HE4, FOLR1, KLK11, WISP1, MDK, CXCL13, MSLN and ADAM8 showed an area under the ROC curve (AUC) of ≥0.70 for discriminating between women diagnosed with ovarian cancer and women who remained cancer-free. All, except ADAM8, had shown at least equal discrimination in previous case-control comparisons. The discrimination of the biomarkers, however, was low for the lag-time of >9-18 months and paired combinations of CA125 with any of the 8 markers did not improve discrimination compared to CA125 alone.
Using pre-diagnostic serum samples, this study identified markers with good discrimination for the lag-time of 0-9 months. However, the discrimination was low in blood samples collected more than 9 months prior to diagnosis, and none of the markers showed major improvement in discrimination when added to CA125.
Endometrial tumors arise from a hormonally responsive tissue. Defining subtypes by hormone receptor expression might better inform etiology and prediction of patient outcomes. We evaluated the ...potential role of tumor estrogen receptor (ER) and progesterone receptor (PR) expression to define endometrial cancer subtypes.
We measured semi-continuous ER and PR protein expression in tissue specimens from 360 endometrial primary tumors from the Nurses' Health Study. To explore the impact of different definitions of marker positivity, we dichotomized ER and PR expression at different cut points in increments of 5% positive cells. Logistic regression was used to estimate associations between endometrial cancer risk factors, such as body mass index, with dichotomous ER or PR status. Reclassification statistics were used to assess whether adding dichotomous ER or PR status to standard prognostic factors of stage, grade, and histologic type would improve endometrial cancer-specific mortality prediction.
Compared with not being obese, obesity increased the odds of having an ER-positive tumor at cut points of 0% to 20% maximum OR, 2.92; 95% confidence interval (CI), 1.34-6.33 as well as the odds of having a PR-positive tumor at cut points of 70% to 90% (maximum OR, 2.53; 95% CI, 1.36-4.68). Adding dichotomous tumor ER or PR status to the panel of standard predictors did not improve both model discrimination and calibration.
Obesity may be associated with greater endometrial tumor expression of ER and PR. Adding either marker does not appear to improve mortality prediction beyond the standard predictors.
Body mass index might explain some of the biological variation among endometrial tumors.
.
PDF
