Variability Of Biomarkers Research Articles

Evaluating reproducibility of AI algorithms in digital pathology with DAPPER.

Artificial Intelligence is exponentially increasing its impact on healthcare. As deep learning is mastering computer vision tasks, its application to digital pathology is natural, with the promise of aiding in routine reporting and standardizing results across trials. Deep learning features inferred from digital pathology scans can improve validity and robustness of current clinico-pathological features, up to identifying novel histological patterns, e.g., from tumor infiltrating lymphocytes. In this study, we examine the issue of evaluating accuracy of predictive models from deep learning features in digital pathology, as an hallmark of reproducibility. We introduce the DAPPER framework for validation based on a rigorous Data Analysis Plan derived from the FDA’s MAQC project, designed to analyze causes of variability in predictive biomarkers. We apply the framework on models that identify tissue of origin on 787 Whole Slide Images from the Genotype-Tissue Expression (GTEx) project. We test three different deep learning architectures (VGG, ResNet, Inception) as feature extractors and three classifiers (a fully connected multilayer, Support Vector Machine and Random Forests) and work with four datasets (5, 10, 20 or 30 classes), for a total of 53, 000 tiles at 512 × 512 resolution. We analyze accuracy and feature stability of the machine learning classifiers, also demonstrating the need for diagnostic tests (e.g., random labels) to identify selection bias and risks for reproducibility. Further, we use the deep features from the VGG model from GTEx on the KIMIA24 dataset for identification of slide of origin (24 classes) to train a classifier on 1, 060 annotated tiles and validated on 265 unseen ones. The DAPPER software, including its deep learning pipeline and the Histological Imaging—Newsy Tiles (HINT) benchmark dataset derived from GTEx, is released as a basis for standardization and validation initiatives in AI for digital pathology.

The progress of research on the immune pathogenesis and biomarkers in optic neuritis related to neuromyelitis optica

The idiopathic optic neuritis (ION) which is related to neuromyelitis optica (NMO) and neuromyelitis optica spectrum disorders (NMOSD) is called optic neuritis related to neuromyelitis optica (NMO-ON). Because of the high rates of blindness, disability and fatality of NMO, the heterogeneous clinical presentation, severity of neurologic disability following relapses, and variability of therapeutic responses, reliable and sensitive biomarkers for onset, relapse, and progression in NMO are urgently needed. Currently, detecting aquaporin-4 (AQP4) antibodies (AQP4-IgG or NMO-IgG) in serum is employed as the major supporting approach for the diagnosis of seropositive NMO, however, AQP4-IgG seronegativity in 10% to 25% of NMO patients suggests that there are several other factors involved in NMO immunopathogenesis. Collaborative international studies hold great promise for establishing and validating biomarkers of NMO. This article discusses known and potential biomarkers for NMO. The biomarkers of NMO maybe the potential biomarkers of NMO-ON, for ION is the initial presentation and the earliest stage. (Chin J Ophthalmol, 2019, 55:228-233).

Biomonitoring and Nonpersistent Chemicals-Understanding and Addressing Variability and Exposure Misclassification.

We offer here a review of intraindividual variability in urinary biomarkers for assessing exposure to nonpersistent chemicals. We provide thoughts on how to better evaluate exposure to nonpersistent chemicals. We summarized reported values of intraclass correlation coefficients and found that most values fall into categories that indicate only poor to good reproducibility. Even within the "good" classification, a large percentage of study participants is likely to be misclassified as to their exposure. There is sufficient information to support the statement that studies using only one spot measurement of a nonpersistent chemical will be unreliable. It is unequivocal that multiple samples have to be collected over a period of toxicological relevance and with consideration of exposure patterns. Sponsors of research and researchers themselves should be vocal about ensuring that sufficient resources are made available to properly characterize exposures when studying nonpersistent chemicals. Otherwise, we will continue to see an ever-growing body of literature yielding inconsistent and/or uninterpretable results.

Potential of a statistical approach for the standardization of multicenter diffusion tensor data: A phantom study

Diffusion tensor imaging (DTI) parameters, such as fractional anisotropy (FA), allow examining the structural integrity of the brain. However, the true value of these parameters may be confounded by variability in MR hardware, acquisition parameters, and image quality. To examine the effects of confounding factors on FA and to evaluate the feasibility of statistical methods to model and reduce multicenter variability. Longitudinal multicenter study. DTI single strand phantom (HQ imaging). 3T diffusion tensor imaging. Thirteen European imaging centers participated. DTI scans were acquired every 6 months and whenever maintenance or upgrades to the system were performed. A total of 64 scans were acquired in 2 years, obtained by three scanner vendors, using six individual head coils, and 12 software versions. The variability in FA was assessed by the coefficients of variation (CoV). Several linear mixed effects models (LMEM) were developed and compared by means of the Akaike Information Criterion (AIC). The CoV was 2.22% for mean FA and 18.40% for standard deviation of FA. The variables "site" (P = 9.26 × 10-5 ), "vendor" (P = 2.18 × 10-5 ), "head coil" (P = 9.00 × 10-4 ), "scanner drift," "bandwidth" (P = 0.033), "TE" (P = 8.20 × 10-6 ), "SNR" (P = 0.029) and "mean residuals" (P = 6.50 × 10-4 ) had a significant effect on the variability in mean FA. The variables "site" (P = 4.00 × 10-4 ), "head coil" (P = 2.00 × 10-4 ), "software" (P = 0.014), and "mean voxel outlier intensity count" (P = 1.10 × 10-4 ) had a significant effect on the variability in standard deviation of FA. The mean FA was best predicted by an LMEM that included "vendor" and the interaction term of "SNR" and "head coil" as model factors (AIC -347.98). In contrast, the standard deviation of FA was best predicted by an LMEM that included "vendor," "bandwidth," "TE," and the interaction term between "SNR" and "head coil" (AIC -399.81). Our findings suggest that perhaps statistical models seem promising to model the variability in quantitative DTI biomarkers for clinical routine and multicenter studies. 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:955-965.

How stable is oxidative stress level? An observational study of intra- and inter-individual variability in urinary oxidative stress biomarkers of DNA, proteins, and lipids in healthy individuals

Oxidative stress in humans is affected by the health and nutritional status as well as exposure to external environmental factors. To evaluate the effects of external factors, an assessment of baseline levels as well as diurnal variations in oxidative stress status of healthy individuals is needed. In this study, we examined intra- and inter-individual variability of oxidative stress biomarkers (OSBs) of lipids (malondialdehyde [MDA] and four F2-isoprostane isomers, namely, 8-isoprostaglandinF2α [8-PGF2α], 11β-prostaglandinF2α [11-PGF2α], 15(R)-prostaglandinF2α [15-PGF2α], and 8-iso,15(R)-prostaglandinF2α [8,15-PGF2α]); proteins (o,o′-dityrosine [diY]); and DNA (8-hydroxy-2′-deoxyguanosine [8-OHdG]) in urine from healthy individuals. The significance of creatinine correction, which is typically used to account for urinary dilution, on OSB concentrations was evaluated. Analysis of 515 urine samples, collected longitudinally from 19 healthy individuals daily for over a month, showed inter-individual coefficient of variation (CV) in concentrations from 112% for MDA to 272% for 15-PGF2α. Intra-individual CV in concentrations ranged from 29% for 8-OHdG to 149% for 15-PGF2α. MDA was the most abundant OSB found in urine. The intra- and inter-individual variability in F2-isoprostane concentrations were higher than the values calculated for diY, 8-OHdG, and MDA. All seven OSB concentrations were significantly correlated with each other and with creatinine. Creatinine normalization of OSB concentrations improved predictability in OSB concentrations over time. Our results suggest that 8-OHdG, showing the highest ICC (0.96), yielded more reproducible measurements with a low CV, and is the most suitable biomarker of OSB in spot urine samples. The measured concentrations and diurnal variability in urinary OSB levels in healthy individuals reported in this study are useful as a benchmark for future toxicological and epidemiological studies.

Correlation and temporal variability of urinary biomarkers of chemicals among couples: Implications for reproductive epidemiological studies

BackgroundExposure to some environmental chemicals is ubiquitous and linked to a variety of adverse outcomes, including children's health. While few studies have assessed the contribution of both male and female exposures to children's health, understanding the patterns of couple's exposure is needed to understand their joint effects. ObjectiveWe assessed the correlation patterns between male and female partners' concentrations of 37 environmental chemical biomarkers. We also assessed the temporal reliability of the biomarkers within couples. MethodsWe calculated Spearman pairwise correlations between specific gravity adjusted urinary biomarker concentrations and hair mercury concentrations among 380 couples enrolled in the Environment and Reproductive Health (EARTH) study at the Massachusetts General Hospital Fertility Center (2004–2017). We calculated intra-class correlation coefficients (ICCs) for couple's biomarkers to assess the temporal variability of these exposures within a couple using multiple paired-samples from couples. ResultsAll biomarkers were positively correlated within couples (range: 0.05 for tert-butylphenyl phenyl phosphate to 0.66 for triclosan). In general, the biomarkers with the highest within couple correlation were those of chemicals for which diet (e.g., di(2-ethylhexyl) phthalate), personal care products use (e.g., triclosan, benzophenone-3), and the indoor environment (e.g., 2,5-dichlorophenol) are considered primary exposure sources. Most other biomarkers were moderately correlated (0.3–<0.6). Similar patterns of temporal reliability were observed across biomarkers. ConclusionsUrinary concentrations of several biomarkers were mostly moderately correlated within couples, suggesting similar exposure sources. Future epidemiological studies should collect samples from both partners to be able to accurately determine the contribution of maternal and paternal exposures to offspring health.

Clinical phenotyping of newly diagnosed type 2 diabetes in Yemen

ObjectiveTo identify clinical phenotypes of type 2 diabetes (T2D) among adults presenting with a first diagnosis of diabetes.Research design and methodsA total of 500 consecutive patients were subject to clinical...

Sequence variants associating with urinary biomarkers.

Urine dipstick tests are widely used in routine medical care to diagnose kidney and urinary tract and metabolic diseases. Several environmental factors are known to affect the test results, whereas the effects of genetic diversity are largely unknown. We tested 32.5 million sequence variants for association with urinary biomarkers in a set of 150 274 Icelanders with urine dipstick measurements. We detected 20 association signals, of which 14 are novel, associating with at least one of five clinical entities defined by the urine dipstick: glucosuria, ketonuria, proteinuria, hematuria and urine pH. These include three independent glucosuria variants at SLC5A2, the gene encoding the sodium-dependent glucose transporter (SGLT2), a protein targeted pharmacologically to increase urinary glucose excretion in the treatment of diabetes. Two variants associating with proteinuria are in LRP2 and CUBN, encoding the co-transporters megalin and cubilin, respectively, that mediate proximal tubule protein uptake. One of the hematuria-associated variants is a rare, previously unreported 2.5 kb exonic deletion in COL4A3. Of the four signals associated with urine pH, we note that the pH-increasing alleles of two variants (POU2AF1, WDR72) associate significantly with increased risk of kidney stones. Our results reveal that genetic factors affect variability in urinary biomarkers, in both a disease dependent and independent context.

The acute efficacy of antipsychotics in schizophrenia: a review of recent meta-analyses.

Schizophrenia is the eighth leading cause of disability worldwide in people aged 15-44 years. Before antidopaminergic antipsychotics were introduced in the 1950s, no effective medications existed for the treatment of schizophrenia. This review summarizes key meta-analytic findings regarding antipsychotic efficacy in the acute treatment of schizophrenia, including clozapine in treatment-resistant patients. In the most comprehensive meta-analysis of randomized controlled trials conducted in multi-episode schizophrenia, antipsychotics outperformed placebo regarding total symptoms, positive symptoms, negative symptoms, depressive symptoms, quality of life and social functioning. Amongst these outcomes, the standardized mean difference for overall symptoms was largest, that is, 0.47 (95% credible interval = 0.42-0.51), approaching a medium effect size, being reduced to 0.38 when publication bias and small-trial effects were accounted for. A comparison of two meta-analyses indicated that first-episode patients, compared with multi-episode patients, were more likely to have at least minimal treatment response [⩾20% Positive and Negative Syndrome Scale (PANSS)/Brief Psychiatric Rating Scale (BPRS) score reduction: 81% versus 51%] and good response (⩾50% PANSS/BPRS score reduction: 52% versus 23%). In multi-episode schizophrenia, no response or worsening after 2 weeks of a therapeutic antipsychotic dose was highly predictive of not achieving a good response at endpoint (median treatment = 6 weeks: specificity = 86%; positive predictive value = 90%), suggesting a change in treatment should be considered in such cases. In first-episode psychosis, adequately dosed antipsychotic treatment trials for more than 2 weeks are recommended before using no response or worsening as a decision point for aborting a given antipsychotic. In clearly defined treatment-resistant schizophrenia, clozapine generally outperformed other antipsychotics, especially when dosed appropriately (target = 3-6 months' duration; trough clozapine level ⩾350-400 μg/L) with a response rate (⩾20% PANSS/BPRS) of 33% by 3 months of treatment. High antipsychotic doses and psychotropic combinations are unlikely to be superior to standard doses of antipsychotic monotherapy. Acute antipsychotic efficacy in schizophrenia depends on the targeted symptom domain (greater efficacy: total and positive symptoms, lesser efficacy: negative symptoms, depressive symptoms, social functioning and quality of life). Greater antipsychotic efficacy is associated with higher total baseline symptom severity, treatment-naïveté/first-episode status, shorter illness duration, and trials that are nonindustry sponsored and that have a lower placebo effect. The heterogeneity of antipsychotic response across individuals and key symptom domains, the considerable degree of nonresponse/treatment resistance in multi-episode patients, and the adverse effect potential of antipsychotics are major limitations, underscoring the need to develop new medications for the treatment of schizophrenia. Drug development should include matching patient subgroups, which are identified by means of clinical and biomarker variables, to mechanisms of action of novel medications, targeting specific symptom domains, and investigating mechanisms of action other than dopaminergic blockade.

Use of integrated biomarker indexes for assessing the impact of receiving waters on a native neotropical teleost fish

In the field of aquatic ecotoxicology, indexes obtained from a battery of biomarkers have proved to be a useful tool for assessing quantifiable and integrated health responses of organisms exposed to pollutants. The objective of this work was to evaluate the effects of exposure to the Reconquista River water (RR) on adults of Cnesterodon decemmaculatus using different integrated indexes. We conducted a 12-d laboratory assay involving the exposure of fish to RR, a negative control (moderately hard water - MHW medium), and a positive control (for genotoxicity with MHW + Cyclophosphamide, CP). There were measured metabolic (food intake and specific assimilation, specific metabolic rate, oxygen extraction efficiency, ammonia excretion, and ammonia quotient), genotoxic (comet assay, micronucleus test, and nuclear abnormalities), morphological variables (total length, body and liver weight) and biochemical variables (Electron Transport System - ETS, Acetylcholinesterase activity - AChE, Catalase - CAT, Glutathione-S-transferase - GST, Glutathione content - GSH and tissue proteins). These variables were grouped into different indexes: morphological (Condition Factor - K and Liver Somatic Index-LSI), metabolic (Scope for Growth-SFG), genetic damage (GDI) and integrated biomarker response - IBR (AChE brain, CAT, GST and GSH liver, GSH gills, ETS muscle) indexes. Results indicated that RR water induced metabolic, biochemical and genetic damages. The SFG, GDI and IBR were suitable to assess the effects of exposure to an environmental sample in an integrated approach, reducing uncertainty due to inherent biomarker variability. These indexes have emerged as promising tools for environmental monitoring studies.

Variability of Urinary Phthalate Metabolite, Bisphenol, and Ultraviolet Filter Concentrations across Sensitive Windows of Human Reproduction

Background: Pre-pregnancy and early pregnancy levels of phthalate, ultraviolet filter, and bisphenol exposure may be associated with adverse reproductive health endpoints. Characterizing variability across sensitive windows of human fecundity can assist in guiding epidemiologic study design of these exposures. In particular, no prior studies have characterized non-persistent endocrine disrupting chemicals across sensitive windows of human reproduction.Methods: We characterized the variability of 12 urinary phthalate metabolites, 6 bisphenol, and 5 ultraviolet filter concentrations prior to and during early pregnancy from 501 women with 1-4 samples per person collected from 2005-2009. Couples were recruited after discontinuing contraception prior to attempting a pregnancy and were followed daily until pregnant. The 343 (68%) women who became pregnant were followed daily through 7 weeks post-conception. We characterized chemical biomarker variability using intraclass correlation coefficients (ICCs) for women from the cohort overall, and by pregnancy status and race/ethnicity.Results: All ICCs (95% CIs) were &amp;lt;0.50 and varied by chemical class (in descending order): 0.46 (0.39, 0.52) for mEP, 0.36 (0.28, 0.43) for BP-1, 0.32 (0.24, 0.39) for BP-3, and 0.26 (0.18, 0.34) for mBP. Several phthalates and one benzophenone had lower reliability (ICC 0.20 to 0.29): mCPP, mBP, mibP, mCHP, mCMHP, and 4-OH-BP. All bisphenols measured were quite variable (ICC -0.11 to 0.01). We did not find substantial differences across ICCs when data were stratified by pregnancy status and race/ethnicity.Conclusion: The observed reliability was fair for monoethyl phthalate and poor for all others (ICC&amp;lt;0.4). A single measurement of non-persistent EDCs does not appear to reliably capture exposures over sensitive windows. To this end, longitudinal measurements are needed to ensure the validity of findings relative to these exposures and human fecundity and fertility.

Maternal Obesity Affects Cardiac Remodeling and Recovery in Women with Peripartum Cardiomyopathy.

To examine the association between maternal obesity on left ventricular (LV) size and recovery in women with peripartum cardiomyopathy (PPCM). This was a prospective analysis of 100 women enrolled within 13 weeks of PPCM diagnosis and followed for a year in the Investigation of Pregnancy Associated Cardiomyopathy study. Adiposity was defined by standard body mass index (BMI) definitions for under/normal weight, overweight, and obesity. Demographic, clinical, and biomarker variables were compared across weight categories. LV end-diastolic diameter (LVEDD) and ejection fraction were measured at entry, 6, and 12 months postpartum. Multivariable regression models examined the relationship between adiposity, LV size, and leptin levels with cardiac recovery at 6 and 12 months postpartum. Obese and nonobese women had similar LV dysfunction at entry. Obese women had greater LV size and less LV recovery at 6 and 12 months postpartum. BMI was positively associated with leptin and ventricular diameter. Greater BMI at entry remained associated with less ventricular recovery at 6 months (p = 0.02) in adjusted race-stratified models. LVEDD at entry predicted lower ejection fraction at 6 months (p < 0.001) and similarly at 12 months. Obese women with PPCM had greater cardiac remodeling, higher leptin levels, and diminished cardiac recovery.

Validation of a simplified in vitro Transwell® model of the alveolar surface to assess host immunity induced by different morphotypes of Aspergillus fumigatus

Interactions between fungal pathogens such as Aspergillus fumigatus with host alveolar epithelium and innate immune cells are crucial in the defense against opportunistic fungal infections. In this study a simplified Transwell® system with a confluent layer of A549 cells acted as a model for the alveolar surface. A. fumigatus and dendritic cells were added to simulate the spatial and cellular complexity in the alveolus. Fungal growth into the lower chamber was validated by galactomannan assays. Addition of moDCs to the upper chamber led to a reduced GM signal and fungal growth, indicating moDC antifungal activity. Minimal cell death was documented by analyses of lactate dehydrogenase concentrations and pro-apoptotic gene expression. Measurement of trans-epithelial dextran blue movement confirmed tightness of the epithelial barrier even in presence of A. fumigatus. Cytokine measurements in supernatants from both chambers of the Transwell® system documented distinct response patterns during early and late stages of epithelial invasion, with A549 cells appearing to make a minimal contribution to cytokine release. Concentrations of cytokines in the lower chamber varied distinctly from the upper chamber, depending on the molecular weight of the cytokines. Low inter-assay variability of fungal biomarkers and cytokines was confirmed, highlighting that in vitro models closely mimicking conditions in the human lung can facilitate reproducible measurement of the dynamics of cytokine release and fungal penetration of host epithelia.

Toward Capturing the Exposome: Exposure Biomarker Variability and Coexposure Patterns in the Shared Environment.

Many factors affect the variation in the exposome. We examined the influence of shared household and partner’s sex in relation to the variation in 128 endocrine disrupting chemical (EDC) exposures among couples. In a cohort comprising of 501 couples trying for pregnancy, we measured 128 (13 chemical classes) persistent and nonpersistent EDCs and estimated 1) sex-specific differences; 2) variance explained by shared household; and 3) Spearman’s rank correlation coefficients (rs) for females, males, and couples’ exposures. Sex was correlated with 8 EDCs including per- and polyfluoroalkyl substances (PFASs) (p < 0.05). Shared household explained 43% and 41% of the total variance for PFASs and blood metals, respectively, but less than 20% for the remaining 11 EDC classes. Coexposure patterns of the exposome were similar between females and males, with within-class rs higher for persistent than for nonpersistent chemicals. Median rss of polybrominated compounds and urine metalloids were 0.45 and 0.09, respectively, for females (0.41 and 0.08 for males; 0.21 and 0.04 for couples). Our findings suggest that individual, rather than shared environment, could be a major factor influencing the covariation of the exposome. Understanding the correlations of exposures has important analytical and sampling implications for exposomics research.

A Pharmacometabolomic Approach to Predict Response to Metformin in Early-Phase Type 2 Diabetes Mellitus Patients.

Metformin is a first-line medication for type 2 diabetes mellitus (T2DM). Based on its universal use, the consideration of inter-individual variability and development of predictive biomarkers are clinically significant. We aimed to identify endogenous markers of metformin responses using a pharmacometabolomic approach. Twenty-nine patients with early-phase T2DM were enrolled and orally administered metformin daily for 6 months. A total of 22 subjects were included in the final analysis. Patients were defined as responders or non-responders based on changes in their glycated haemoglobin A1c (HbA1c) from baseline, over 3 months. Urine metabolites at baseline, as well as at the 3 and 6 month follow-ups after the start of treatment were analysed using gas chromatography-mass spectrometry and evaluated with multivariate analyses. Metabolites distinguishable between the two response groups were obtained at baseline, as well as at the 3 and 6 month follow-ups, and significantly different metabolites were listed as markers of metformin response. Among the identified metabolites, citric acid, myoinositol, and hippuric acid levels showed particularly significant differences between the non-responder and responder groups. We thus identified different metabolite profiles in the two groups of T2DM patients after metformin administration, using pharmacometabolomics. These results might facilitate a better understanding and prediction of metformin response and its variability in individual patients.

MeDIP combined with in-solution targeted enrichment followed by NGS: Inter-individual methylation variability of fetal-specific biomarkers and their implementation in a proof of concept study for NIPT

DNA methylation is the most characterized epigenetic process exhibiting stochastic variation across different tissues and individuals. In non-invasive prenatal testing (NIPT) fetal specific methylated regions can potentially be used as biomarkers for the accurate detection of fetal aneuploidies. The aim of this study was the investigation of inter-individual methylation variability of previously reported fetal-specific markers and their implementation towards the development of a novel NIPT assay for the detection of trisomies 13, 18, and 21. Methylated DNA Immunoprecipitation (MeDIP) combined with in-solution targeted enrichment followed by NGS was performed in 29 CVS and 27 female plasma samples to assess inter-individual methylation variability of 331 fetal-specific differentially methylated regions (DMRs). The same approach was implemented for the NIPT of trisomies 13, 18 and 21 using spiked-in (n = 6) and pregnancy samples (n = 44), including one trisomy 13, one trisomy 18 and four trisomy 21. Despite the variability of DMRs, CVS samples showed statistically significant hypermethylation (p<2e-16) compared to plasma samples. Importantly, our assay correctly classified all euploid and aneuploid cases without any false positive results (n = 44). This work provides the starting point for the development of a NIPT assay based on a robust set of fetal specific biomarkers for the detection of fetal aneuploidies. Furthermore, the assay’s targeted nature significantly reduces the analysis cost per sample while providing high read depth at regions of interest increasing significantly its accuracy.

Biomarker assessment and combination with differential covariate effects and an unknown gold standard, with an application to Alzheimer’s disease

The continued efforts to evaluate biomarkers’ predictive abilities and identify optimal biomarker combinations are often challenged by the absence of a gold standard, that is, the true disease status. Current methods that address this issue are mostly developed for binary or ordinal diagnostic tests, which do not fully utilize information provided by continuous biomarkers, or require strong parametric assumptions. Moreover, limited methods exist to allow for the inclusion of covariates—despite their crucial role in facilitating the accurate evaluation of biomarkers. In this paper, we proposed a latent profile approach to evaluating diagnostic accuracy of biomarkers without a gold standard. The method allows for flexible biomarker distributions and incorporation of previous knowledge about risk factors while simultaneously permitting researchers to model paticipants’ characteristics that putatively affect biomarker levels, and therefore provides information needed to develop more personalized diagnostic procedures. Additionally, the proposed method presents a potential strategy for biomarker combination when gold standard information is unavailable, as it derives a composite risk score for the underlying disease status. The method is applied to evaluate different cerebral spinal fluid (CSF) biomarkers for Alzheimer’s disease (AD) detection. The results show that CSF biomarkers hold significant potential for facilitating early AD detection and for continuous disease monitoring. Furthermore, they call attention to biomarker variability in subgroups and reexamination of CSF biomarker distributions. Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database.

Smoking and Physical Activity Explain the Increased Mortality Risk Following Marital Separation and Divorce: Evidence From the English Longitudinal Study of Ageing.

Marital separation and divorce are associated with an increased risk of early mortality, but the specific biobehavioral pathways that explain this association remain largely unknown. This study sought to identify the putative psychological, behavioral, and biomarker variables that can help explain the association of being separated or divorced and increased risk for early mortality. Using data from the English Longitudinal Study of Ageing, a representative community sample of aging adults (N = 5,786), we examined the association of marital status and life satisfaction, health behaviors measured 2 years later, biomarkers measured 4 years later, and mortality outcomes from the subsequent 4 years. Consistent with prior literature, older adults who were separated/divorced evidenced greater risk of mortality relative to those in intact marriages over the study period, OR = 1.46, 95% CI [1.15, 1.86]. Marital status was associated with lower levels of life satisfaction, β = -0.22 [-0.25, -0.19] and greater likelihood of smoking 2 years later β = 0.17 [0.13, 0.21]. Lower life satisfaction predicted less frequent physical activity 2 years later, β = 0.07 [0.03, 0.10]. Smoking, but not physical activity, predicted poorer lung functioning 2 years later, β = -0.43 [-0.51, -0.35], and poorer lung function predicted increased likelihood of mortality over the following 4 years, β = -0.15 [-0.27, -0.03]. There was a significant total indirect effect of marital status on mortality through these psychological, behavioral, and biomarker variables, β = 0.03 [0.01, 0.05], which fully explained this mortality risk. For separated/divorced adults, differences in life satisfaction predict health behaviors associated with poorer long-term lung function, and these intermediate variables help explain the association between marital dissolution and increased risk of earlier mortality.

Hydration Biomarker and Plasma Copeptin Variability in Response to Partial Rehydration After Exercise-Induced Dehydration

Hydration Biomarker and Plasma Copeptin Variability in Response to Partial Rehydration After Exercise-Induced Dehydration

Widespread associations between trait conscientiousness and thickness of brain cortical regions

The neural correlates of human personality have been of longstanding interest; however, most studies in the field have relied on modest sample sizes and few replicable results have been reported to date. We investigated relationships between personality and brain gray matter in a sample of generally healthy, older (mean age 73 years) adults from Scotland drawn from the Lothian Birth Cohort 1936. Participants (N = 578) completed a brain MRI scan and self-reported Big Five personality trait measures. Conscientiousness trait scores were positively related to brain cortical thickness in a range of regions, including bilateral parahippocampal gyrus, bilateral fusiform gyrus, left cingulate gyrus, right medial orbitofrontal cortex, and left dorsomedial prefrontal cortex. These associations – most notably in frontal regions – were modestly-to-moderately attenuated by the inclusion of biomarker variables assessing allostatic load and smoking status. None of the other personality traits showed robust associations with brain cortical thickness, nor did we observe any personality trait associations with cortical surface area and gray matter volume. These findings indicate that brain cortical thickness is associated with conscientiousness, perhaps partly accounted for by allostatic load and smoking status.