The diagnostic and prognostic capabilities of plasma biomarkers in Alzheimer's disease.

INTRODUCTION: This study investigated the diagnostic and disease-monitoring potential of plasma biomarkers in mild cognitive impairment (MCI) and Alzheimer's disease (AD) dementia and cognitively unimpaired (CU) individuals. METHODS: Plasma was analyzed using Simoa assays from 99 CU, 107 MCI, and 103 AD dementia participants. RESULTS: Phosphorylated-tau181 (P-tau181), neurofilament light, amyloid-ß (Aß42/40), Total-tau and Glial fibrillary acidic protein were altered in AD dementia but P-tau181 significantly outperformed all biomarkers in differentiating AD dementia from CU (area under the curve [AUC] = 0.91). P-tau181 was increased in MCI converters compared to non-converters. Higher P-tau181 was associated with steeper cognitive decline and gray matter loss in temporal regions. Longitudinal change of P-tau181 was strongly associated with gray matter loss in the full sample and with Aß measures in CU individuals. DISCUSSION: P-tau181 detected AD at MCI and dementia stages and was strongly associated with cognitive decline and gray matter loss. These findings highlight the potential value of plasma P-tau181 as a non-invasive and cost-effective diagnostic and prognostic biomarker in AD.

Inflammatory biomarkers in Alzheimer's disease plasma.

INTRODUCTION: Plasma biomarkers for Alzheimer's disease (AD) diagnosis/stratification are a "Holy Grail" of AD research and intensively sought; however, there are no well-established plasma markers. METHODS: A hypothesis-led plasma biomarker search was conducted in the context of international multicenter studies. The discovery phase measured 53 inflammatory proteins in elderly control (CTL; 259), mild cognitive impairment (MCI; 199), and AD (262) subjects from AddNeuroMed. RESULTS: Ten analytes showed significant intergroup differences. Logistic regression identified five (FB, FH, sCR1, MCP-1, eotaxin-1) that, age/APOε4 adjusted, optimally differentiated AD and CTL (AUC: 0.79), and three (sCR1, MCP-1, eotaxin-1) that optimally differentiated AD and MCI (AUC: 0.74). These models replicated in an independent cohort (EMIF; AUC 0.81 and 0.67). Two analytes (FB, FH) plus age predicted MCI progression to AD (AUC: 0.71). DISCUSSION: Plasma markers of inflammation and complement dysregulation support diagnosis and outcome prediction in AD and MCI. Further replication is needed before clinical translation.

The interactive effect of demographic and clinical factors on hippocampal volume: A multicohort study on 1958 cognitively normal individuals.

Alzheimer's disease is characterized by hippocampal atrophy. Other factors also influence the hippocampal volume, but their interactive effect has not been investigated before in cognitively healthy individuals. The aim of this study is to evaluate the interactive effect of key demographic and clinical factors on hippocampal volume, in contrast to previous studies frequently investigating these factors in a separate manner. Also, to investigate how comparable the control groups from ADNI, AIBL, and AddNeuroMed are with five population-based cohorts. In this study, 1958 participants were included (100 AddNeuroMed, 226 ADNI, 155 AIBL, 59 BRC, 295 GENIC, 279 BioFiNDER, 398 PIVUS, and 446 SNAC-K). ANOVA and random forest were used for testing between-cohort differences in demographic-clinical variables. Multiple regression was used to study the influence of demographic-clinical variables on hippocampal volume. ANCOVA was used to analyze whether between-cohort differences in demographic-clinical variables explained between-cohort differences in hippocampal volume. Age and global brain atrophy were the most important variables in explaining variability in hippocampal volume. These variables were not only important themselves but also in interaction with gender, education, MMSE, and total intracranial volume. AddNeuroMed, ADNI, and AIBL differed from the population-based cohorts in several demographic-clinical variables that had a significant effect on hippocampal volume. Variability in hippocampal volume in individuals with normal cognition is high. Differences that previously tended to be related to disease mechanisms could also be partly explained by demographic and clinical factors independent from the disease. Furthermore, cognitively normal individuals especially from ADNI and AIBL are not representative of the general population. These findings may have important implications for future research and clinical trials, translating imaging biomarkers to the general population, and validating current diagnostic criteria for Alzheimer's disease and predementia stages.

Disrupted Network Topology in Patients with Stable and Progressive Mild Cognitive Impairment and Alzheimer's Disease.

Recent findings suggest that Alzheimer's disease (AD) is a disconnection syndrome characterized by abnormalities in large-scale networks. However, the alterations that occur in network topology during the prodromal stages of AD, particularly in patients with stable mild cognitive impairment (MCI) and those that show a slow or faster progression to dementia, are still poorly understood. In this study, we used graph theory to assess the organization of structural MRI networks in stable MCI (sMCI) subjects, late MCI converters (lMCIc), early MCI converters (eMCIc), and AD patients from 2 large multicenter cohorts: ADNI and AddNeuroMed. Our findings showed an abnormal global network organization in all patient groups, as reflected by an increased path length, reduced transitivity, and increased modularity compared with controls. In addition, lMCIc, eMCIc, and AD patients showed a decreased path length and mean clustering compared with the sMCI group. At the local level, there were nodal clustering decreases mostly in AD patients, while the nodal closeness centrality detected abnormalities across all patient groups, showing overlapping changes in the hippocampi and amygdala and nonoverlapping changes in parietal, entorhinal, and orbitofrontal regions. These findings suggest that the prodromal and clinical stages of AD are associated with an abnormal network topology.

Association of blood lipids with Alzheimer's disease: A comprehensive lipidomics analysis.

INTRODUCTION: The aim of this study was to (1) replicate previous associations between six blood lipids and Alzheimer's disease (AD) (Proitsi et al 2015) and (2) identify novel associations between lipids, clinical AD diagnosis, disease progression and brain atrophy (left/right hippocampus/entorhinal cortex). METHODS: We performed untargeted lipidomic analysis on 148 AD and 152 elderly control plasma samples and used univariate and multivariate analysis methods. RESULTS: We replicated our previous lipids associations and reported novel associations between lipids molecules and all phenotypes. A combination of 24 molecules classified AD patients with >70% accuracy in a test and a validation data set, and we identified lipid signatures that predicted disease progression (R2 = 0.10, test data set) and brain atrophy (R2 ≥ 0.14, all test data sets except left entorhinal cortex). We putatively identified a number of metabolic features including cholesteryl esters/triglycerides and phosphatidylcholines. DISCUSSION: Blood lipids are promising AD biomarkers that may lead to new treatment strategies.

Protective variant for hippocampal atrophy identified by whole exome sequencing.

We used whole-exome sequencing to identify variants other than APOE associated with the rate of hippocampal atrophy in amnestic mild cognitive impairment. An in-silico predicted missense variant in REST (rs3796529) was found exclusively in subjects with slow hippocampal volume loss and validated using unbiased whole-brain analysis and meta-analysis across 5 independent cohorts. REST is a master regulator of neurogenesis and neuronal differentiation that has not been previously implicated in Alzheimer's disease. These findings nominate REST and its functional pathways as protective and illustrate the potential of combining next-generation sequencing with neuroimaging to discover novel disease mechanisms and potential therapeutic targets.

Quantitative validation of a visual rating scale for frontal atrophy: associations with clinical status, APOE e4, CSF biomarkers and cognition.

OBJECTIVES: To validate a visual rating scale of frontal atrophy with quantitative imaging and study its association with clinical status, APOE ε4, CSF biomarkers, and cognition. METHODS: The AddNeuroMed and ADNI cohorts were combined giving a total of 329 healthy controls, 421 mild cognitive impairment patients, and 286 Alzheimer's disease (AD) patients. Thirty-four patients with frontotemporal dementia (FTD) were also included. Frontal atrophy was assessed with the frontal sub-scale of the global cortical atrophy scale (GCA-F) on T1-weighted images. Automated imaging markers of cortical volume, thickness, and surface area were evaluated. Manual tracing was also performed. RESULTS: The GCA-F scale reliably reflects frontal atrophy, with orbitofrontal, dorsolateral, and motor cortices being the regions contributing most to the GCA-F ratings. GCA-F primarily reflects reductions in cortical volume and thickness, although it was able to detect reductions in surface area too. The scale showed significant associations with clinical status and cognition. CONCLUSION: The GCA-F scale may have implications for clinical practice as supportive diagnostic tool for disorders demonstrating predominant frontal atrophy such as FTD and the executive presentation of AD. We believe that GCA-F is feasible for use in clinical routine for the radiological assessment of dementia and other disorders. KEY POINTS: • The GCA-F visual rating scale reliably reflects frontal brain atrophy. • Orbitofrontal, dorsolateral, and motor cortices are the most contributing regions. • GCA-F shows significant associations with clinical status and cognition. • GCA-F may be supportive diagnostic tool for disorders demonstrating predominant frontal atrophy. • GCA-F may be feasible for use in radiological routine.

Prevalence and prognosis of Alzheimer's disease at the mild cognitive impairment stage.

Three sets of research criteria are available for diagnosis of Alzheimer's disease in subjects with mild cognitive impairment: the International Working Group-1, International Working Group-2, and National Institute of Aging-Alzheimer Association criteria. We compared the prevalence and prognosis of Alzheimer's disease at the mild cognitive impairment stage according to these criteria. Subjects with mild cognitive impairment (n = 1607), 766 of whom had both amyloid and neuronal injury markers, were recruited from 13 cohorts. We used cognitive test performance and available biomarkers to classify subjects as prodromal Alzheimer's disease according to International Working Group-1 and International Working Group-2 criteria and in the high Alzheimer's disease likelihood group, conflicting biomarker groups (isolated amyloid pathology or suspected non-Alzheimer pathophysiology), and low Alzheimer's disease likelihood group according to the National Institute of Ageing-Alzheimer Association criteria. Outcome measures were the proportion of subjects with Alzheimer's disease at the mild cognitive impairment stage and progression to Alzheimer's disease-type dementia. We performed survival analyses using Cox proportional hazards models. According to the International Working Group-1 criteria, 850 (53%) subjects had prodromal Alzheimer's disease. Their 3-year progression rate to Alzheimer's disease-type dementia was 50% compared to 21% for subjects without prodromal Alzheimer's disease. According to the International Working Group-2 criteria, 308 (40%) subjects had prodromal Alzheimer's disease. Their 3-year progression rate to Alzheimer's disease-type dementia was 61% compared to 22% for subjects without prodromal Alzheimer's disease. According to the National Institute of Ageing-Alzheimer Association criteria, 353 (46%) subjects were in the high Alzheimer's disease likelihood group, 49 (6%) in the isolated amyloid pathology group, 220 (29%) in the suspected non-Alzheimer pathophysiology group, and 144 (19%) in the low Alzheimer's disease likelihood group. The 3-year progression rate to Alzheimer's disease-type dementia was 59% in the high Alzheimer's disease likelihood group, 22% in the isolated amyloid pathology group, 24% in the suspected non-Alzheimer pathophysiology group, and 5% in the low Alzheimer's disease likelihood group. Our findings support the use of the proposed research criteria to identify Alzheimer's disease at the mild cognitive impairment stage. In clinical settings, the use of both amyloid and neuronal injury markers as proposed by the National Institute of Ageing-Alzheimer Association criteria offers the most accurate prognosis. For clinical trials, selection of subjects in the National Institute of Ageing-Alzheimer Association high Alzheimer's disease likelihood group or the International Working Group-2 prodromal Alzheimer's disease group could be considered.

The Effect of Age Correction on Multivariate Classification in Alzheimer's Disease, with a Focus on the Characteristics of Incorrectly and Correctly Classified Subjects.

The similarity of atrophy patterns in Alzheimer's disease (AD) and in normal aging suggests age as a confounding factor in multivariate models that use structural magnetic resonance imaging (MRI) data. To study the effect and compare different age correction approaches on AD diagnosis and prediction of mild cognitive impairment (MCI) progression as well as investigate the characteristics of correctly and incorrectly classified subjects. Data from two multi-center cohorts were included in the study [AD = 297, MCI = 445, controls (CTL) = 340]. 34 cortical thickness and 21 subcortical volumetric measures were extracted from MRI. The age correction approaches involved: using age as a covariate to MRI-derived measures and linear detrending of age-related changes based on CTL measures. Orthogonal projections to latent structures was used to discriminate between AD and CTL subjects, and to predict MCI progression to AD, up to 36-months follow-up. Both age correction approaches improved models' quality in terms of goodness of fit and goodness of prediction, as well as classification and prediction accuracies. The observed age associations in classification and prediction results were effectively eliminated after age correction. A detailed analysis of correctly and incorrectly classified subjects highlighted age associations in other factors: ApoE genotype, global cognitive impairment and gender. The two methods for age correction gave similar results and show that age can partially masks the influence of other aspects such as cognitive impairment, ApoE-e4 genotype and gender. Age-related brain atrophy may have a more important association with these factors than previously believed.

Measuring Global Brain Atrophy with the Brain Volume/Cerebrospinal Fluid Index: Normative Values, Cut-Offs and Clinical Associations.

BACKGROUND: Global brain atrophy is present in normal aging and different neurodegenerative disorders such as Alzheimer's disease (AD) and is becoming widely used to monitor disease progression. SUMMARY: The brain volume/cerebrospinal fluid index (BV/CSF index) is validated in this study as a measurement of global brain atrophy. We tested the ability of the BV/CSF index to detect global brain atrophy, investigated the influence of confounders, provided normative values and cut-offs for mild, moderate and severe brain atrophy, and studied associations with different outcome variables. A total of 1,009 individuals were included [324 healthy controls, 408 patients with mild cognitive impairment (MCI) and 277 patients with AD]. Magnetic resonance images were segmented using FreeSurfer, and the BV/CSF index was calculated and studied both cross-sectionally and longitudinally (1-year follow-up). Both AD patients and MCI patients who progressed to AD showed greater global brain atrophy compared to stable MCI patients and controls. Atrophy was associated with older age, larger intracranial volume, less education and presence of the ApoE ε4 allele. Significant correlations were found with clinical variables, CSF biomarkers and several cognitive tests. KEY MESSAGES: The BV/CSF index may be useful for staging individuals according to the degree of global brain atrophy, and for monitoring disease progression. It also shows potential for predicting clinical changes and for being used in the clinical routine.

Levels of C-reactive protein (CRP) in elderly patients with unipolar depression - case control analysis.

AIM: C-reactive protein (CRP) is the major acute-phase plasma protein. Studies show that patients with depression have elevated levels of CRP. The aim of the study was to determine differences in CRP serum level in elderly patients with unipolar depression (DEP) compared with non-depressed elderly patients (nonDEP) using case-control analysis. METHODS: Serum level of CRP was measured in 404 (DEP: n = 202, nonDEP: n = 202) Caucasian inpatients aged ≥60 (350 women, 86.7%; mean age = 76.7 years). RESULTS: Mean CRP level in the study groups was: DEP 2.67 ± 2.56 mg/dL, nonDEP 2.41 ± 2.19 mg/dL, the difference was not significant (p = 0.96). The overall rate of being above the high level of CRP (set at 3.0 mg/L) was 33.2% for DEP and 29.2% for nonDEP groups (p = 0.39). It was also found that, in the whole study group, CRP level was not correlated with age (p = 0.10). CONCLUSIONS: Elderly patients with depression have no increased CRP levels. A high percentage (∼30%) of all subjects had a CRP level >3 mg/L, which is the cut-off point for increased cardiovascular risk.

Automated Hippocampal Subfield Measures as Predictors of Conversion from Mild Cognitive Impairment to Alzheimer's Disease in Two Independent Cohorts.

Previous studies have shown that hippocampal subfields may be differentially affected by Alzheimer's disease (AD). This study used an automated analysis technique and two large cohorts to (1) investigate patterns of subfield volume loss in mild cognitive impairment (MCI) and AD, (2) determine the pattern of subfield volume loss due to age, gender, education, APOE ε4 genotype, and neuropsychological test scores, (3) compare combined subfield volumes to hippocampal volume alone at discriminating between AD and healthy controls (HC), and predicting future MCI conversion to AD at 12 months. 1,069 subjects were selected from the AddNeuroMed and Alzheimer's disease neuroimaging initiative (ADNI) cohorts. Freesurfer was used for automated segmentation of the hippocampus and hippocampal subfields. Orthogonal partial least squares to latent structures (OPLS) was used to train models on AD and HC subjects using one cohort for training and the other for testing and the combined cohort was used to predict MCI conversion. MANCOVA and linear regression analyses showed multiple subfield volumes including Cornu Ammonis 1 (CA1), subiculum and presubiculum were atrophied in AD and MCI and were related to age, gender, education, APOE ε4 genotype, and neuropsychological test scores. For classifying AD from HC, combined subfield volumes achieved comparable classification accuracy (81.7%) to total hippocampal (80.7%), subiculum (81.2%) and presubiculum (80.6%) volume. For predicting MCI conversion to AD combined subfield volumes and presubiculum volume were more accurate (81.1%) than total hippocampal volume. (76.7%).

Serum levels of AgRP protein in patients with schizophrenia on clozapine monotherapy.

AIM: Agouti-related peptide (AgRP) is one of the hypothalamic hormones that works by increasing appetite and decreasing metabolism, thus leading to weight gain. The aim of the study was to find out if AgRP level in subjects with schizophrenia on clozapine monotherapy is higher compared with healthy controls. METHODOLOGY: We determined fasting serum AgRP levels in 24 subjects with schizophrenia on clozapine monotherapy and 24 healthy, age- and sex-matched controls. Biochemical and anthropometric measurements were combined with body composition analysis. RESULTS: There was no difference for AgRP levels between patients taking clozapine and control group (15.00±8.65 vs. 15.33±6.82 pg/mL, p =0.37). We found negative correlations between AgRP levels and total body fat (r =-0.34 and -0.48 in the whole study group and clozapine group, respectively) and positive correlations with lean body mass (r =0.38 and 0.49 in the whole study group and clozapine group, respectively), body water (r =0.34 and 0.49 in the whole study group and clozapine group, respectively) and basal metabolic rate (r =0.42 both in the clozapine and control groups). There were no correlations with age, height, weight, body mass index, fat mass index, abdominal, waist or hip circumferences, waist-hip ratio, blood pressure, total cholesterol, HDL, LDL, triglycerides, uric acid, glucose, insulin, clozapine dose or treatment duration, duration of treatment with antipsychotics and markers for insulin resistance. CONCLUSION: We cannot conclude that treatment with clozapine is associated with increased level of AgRP. We did not find previously described differences in AgRP levels between obese and non-obese subjects or associations between AgRP and various metabolic parameters.

Uric acid levels in patients with schizophrenia on clozapine monotherapy.

BACKGROUND: We tested the hypothesis that uric acid levels are higher in subjects with schizophrenia treated with clozapine than in healthy control and they correlate with anthropometric measurements, laboratory tests and results of bioimpedance analysis of body composition. METHODS: Data for 24 subjects with schizophrenia treated with clozapine and 24 age- and sex-matched healthy volunteers was analyzed. RESULTS: There was no difference of fasting uric acid concentrations between clozapine and control groups (4.5 ± 1.4 vs. 4.3 ± 1.3 mg/dl, P = 0.87). Regarding the whole group, uric acid levels were significantly higher in men (5.2 ± 1.2 vs. 3.6 ± 0.9, P < 0.001). Uric acid levels correlated with weight (R = 0.58, P = 0.003), body mass index (BMI; R = 0.49, P = 0.01), abdominal circumference (R = 0.45, P = 0.03), waist circumference (R = 0.47, P = 0.02), waist-to-hip ratio (R = 0.42, P = 0.04), insulin (R = 0.50, P = 0.01), homoeostasis model assessment of insulin resistance 2 (HOMA2-IR; R = 0.49, P = 0.01), basal metabolic rate (R = 0.56, P = 0.004), lean body mass (R = 0.55, P = 0.005) and body water (R = 0.55, P = 0.005). There were no significant differences of uric acid levels for smoking status, impaired fasting glucose, abdominal obesity, obesity/overweight and dyslipidemia. Uric acid levels did not correlate with age, duration of clozapine treatment, clozapine dose, leg circumference, systolic blood pressure, diastolic blood pressure, total body fat, triglycerides, total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), homocysteine, corrected calcium, glucose and homoeostasis model assessment of insulin resistance 1 (HOMA1-IR). CONCLUSIONS: We did not find significant differences in blood uric acid levels between subjects with schizophrenia and controls. Association with weight, BMI, abdominal and waist circumferences, insulin levels and insulin resistance may support uric acid role as an important cardiovascular risk factor. Association with lean weight may explain why men have higher levels of uric acid than women.

Levels of C-reactive protein (CRP) in patients with schizophrenia, unipolar depression and bipolar disorder.

OBJECTIVE: C-reactive protein (CRP) is the major acute-phase plasma protein. Studies show that patients with various mental disorders have elevated levels of CRP. The aim of the study was to determine differences in CRP serum level in patients with acute schizophrenia, unipolar depression, bipolar depression and bipolar mania. METHOD: Serum level of CRP was measured in 950 Caucasian inpatients (589 women, 62.0%; mean age 50.3 years). RESULTS: Mean concentration of CRP in study groups was: schizophrenia (n = 485) 5.30 mg/l, unipolar depression (n = 319) 5.61 mg/l, bipolar disorder (n = 146) 4.65 mg/l, bipolar depression (n = 114) 3.82 mg/l and bipolar mania (n = 32) 7.36 mg/l. There was no difference for CRP levels between patients with schizophrenia, unipolar depression, bipolar depression and bipolar mania (P = 0.58). The overall rate of being above the high level of CRP (set at 3.0 mg/l) was 35.7% for schizophrenia, 38.6% for unipolar depression, 40.4% for bipolar disorder, 40.4% for bipolar depression and 40.6% for bipolar mania. There were no significant differences in the risk of having high level of CRP between the clinical groups. The rate of patients being above high level was higher in women. We also found that in whole study group CRP level was positively correlated with age (P = 0.002). CONCLUSIONS: Although there is no statistically significant difference in CRP serum level between patients with schizophrenia, unipolar depression, bipolar depression and bipolar mania, our results show that more than one-third (37.4%) of all subjects had CRP level > 3 mg/l, which is the cut-off point for high cardiovascular risk.

Genetic predisposition to increased blood cholesterol and triglyceride lipid levels and risk of Alzheimer disease: a Mendelian randomization analysis.

BACKGROUND: Although altered lipid metabolism has been extensively implicated in the pathogenesis of Alzheimer disease (AD) through cell biological, epidemiological, and genetic studies, the molecular mechanisms linking cholesterol and AD pathology are still not well understood and contradictory results have been reported. We have used a Mendelian randomization approach to dissect the causal nature of the association between circulating lipid levels and late onset AD (LOAD) and test the hypothesis that genetically raised lipid levels increase the risk of LOAD. METHODS AND FINDINGS: We included 3,914 patients with LOAD, 1,675 older individuals without LOAD, and 4,989 individuals from the general population from six genome wide studies drawn from a white population (total n=10,578). We constructed weighted genotype risk scores (GRSs) for four blood lipid phenotypes (high-density lipoprotein cholesterol [HDL-c], low-density lipoprotein cholesterol [LDL-c], triglycerides, and total cholesterol) using well-established SNPs in 157 loci for blood lipids reported by Willer and colleagues (2013). Both full GRSs using all SNPs associated with each trait at p<5×10-8 and trait specific scores using SNPs associated exclusively with each trait at p<5 × 10-8 were developed. We used logistic regression to investigate whether the GRSs were associated with LOAD in each study and results were combined together by meta-analysis. We found no association between any of the full GRSs and LOAD (meta-analysis results: odds ratio [OR]=1.005, 95% CI 0.82-1.24, p = 0.962 per 1 unit increase in HDL-c; OR=0.901, 95% CI 0.65-1.25, p=0.530 per 1 unit increase in LDL-c; OR=1.104, 95% CI 0.89-1.37, p=0.362 per 1 unit increase in triglycerides; and OR=0.954, 95% CI 0.76-1.21, p=0.688 per 1 unit increase in total cholesterol). Results for the trait specific scores were similar; however, the trait specific scores explained much smaller phenotypic variance. CONCLUSIONS: Genetic predisposition to increased blood cholesterol and triglyceride lipid levels is not associated with elevated LOAD risk. The observed epidemiological associations between abnormal lipid levels and LOAD risk could therefore be attributed to the result of biological pleiotropy or could be secondary to LOAD. Limitations of this study include the small proportion of lipid variance explained by the GRS, biases in case-control ascertainment, and the limitations implicit to Mendelian randomization studies. Future studies should focus on larger LOAD datasets with longitudinal sampled peripheral lipid measures and other markers of lipid metabolism, which have been shown to be altered in LOAD. Please see later in the article for the Editors' Summary.

Identification of cis-regulatory variation influencing protein abundance levels in human plasma.

Proteins are central to almost all cellular processes, and dysregulation of expression and function is associated with a range of disorders. A number of studies in human have recently shown that genetic factors significantly contribute gene expression variation. In contrast, very little is known about the genetic basis of variation in protein abundance in man. Here, we assayed the abundance levels of proteins in plasma from 96 elderly Europeans using a new aptamer-based proteomic technology and performed genome-wide local (cis-) regulatory association analysis to identify protein quantitative trait loci (pQTL). We detected robust cis-associations for 60 proteins at a false discovery rate of 5%. The most highly significant single nucleotide polymorphism detected was rs7021589 (false discovery rate, 2.5 × 10(-12)), mapped within the gene coding sequence of Tenascin C (TNC). Importantly, we identified evidence of cis-regulatory variation for 20 previously disease-associated genes encoding protein, including variants with strong evidence of disease association show significant association with protein abundance levels. These results demonstrate that common genetic variants contribute to the differences in protein abundance levels in human plasma. Identification of pQTLs will significantly enhance our ability to discover and comprehend the biological and functional consequences of loci identified from genome-wide association study of complex traits. This is the first large-scale genetic association study of proteins in plasma measured using a novel, highly multiplexed slow off-rate modified aptamer (SOMAmer) proteomic platform.

Level of thyroid-stimulating hormone (TSH) in patients with acute schizophrenia, unipolar depression or bipolar disorder.

The aim of this study is to investigate differences in thyroid-stimulating hormone (TSH) level in patients with acute schizophrenia, unipolar depression, bipolar depression and bipolar mania. Serum level of TSH was measured in 1,685 Caucasian patients (1,064 women, 63.1%; mean age 46.4). Mean serum TSH concentration was: schizophrenia (n = 769) 1.71 µIU/mL, unipolar depression (n = 651) 1.63 µIU/mL, bipolar disorder (n = 264) 1.86 µIU/mL, bipolar depression (n = 203) 2.00 µIU/mL, bipolar mania (n = 61) 1.38 µIU/mL (H = 11.58, p = 0.009). Depending on the normal range used, the overall rate of being above or below the normal range was 7.9-22.3% for schizophrenia, 13.9-26.0% for unipolar depression, 10.8-27.6% for bipolar disorder, 12.2-28.5% for bipolar depression, and 11.4-24.5% for bipolar mania. We have also found differences in TSH levels between the age groups (≤20, >20 years and ≤40, >40 years and ≤60 years and >60 years). TSH level was negatively correlated with age (r = -0.23, p < 0.001). Weak correlations with age have been found in the schizophrenia (r = -0.21, p < 0.001), unipolar depression (r = -0.23, p < 0.001), bipolar depression (r = -0.25, p = 0.002) and bipolar disorder (r = -0.21, p = 0.005) groups. Our results confirm that there may be a higher prevalence of thyroid dysfunctions in patients with mood disorders (both unipolar and bipolar) and that these two diagnostic groups differ in terms of direction and frequency of thyroid dysfunctions.

Mild cognitive impairment with associated inflammatory and cortisol alterations as independent risk factor for postoperative delirium.

AIMS: The present study aimed to determine the impact of mild cognitive impairment (MCI) on the development of postoperative delirium and, secondly, to assess the association between MCI and raised perioperative cortisol, cytokine, cobalamin and homocysteine levels. METHODS: The study recruited 113 consecutive adult patients scheduled for cardiac surgery with cardiopulmonary bypass. The patients were examined preoperatively with the Montreal Cognitive Assessment and Trail Making Test. A diagnosis of MCI was established based upon the criteria of the National Institute on Aging and Alzheimer's Association. Patients were screened for delirium within the first 5 days postoperatively. RESULTS: MCI was diagnosed in 24.8% of the patients, whereas the frequency of delirium was 36%. A multivariate analysis demonstrated that individuals with MCI were at a significantly higher risk of postoperative delirium (OR = 6.33, p = 0.002). Preoperative cortisol, postoperative cortisol and IL-2 plasma levels were higher in the MCI group as compared to non-MCI subjects. CONCLUSION: MCI is associated with a higher risk of postoperative delirium. Perioperative cortisol and inflammatory alterations observed in MCI may provide a physiological explanation for this increased risk.

Serum levels of desacyl ghrelin in patients with schizophrenia on clozapine monotherapy.

AIM: Desacyl ghrelin is a hormone that might be a functional inhibitor of ghrelin, a potent hunger-stimulating peptide. METHODS: We determined fasting serum desacyl ghrelin levels in 24 subjects with schizophrenia on clozapine monotherapy and 24 healthy, age- and sex-matched controls. Biochemical and anthropometric measurements were combined with body composition determined using bioelectric impedance analysis. RESULTS: There were no differences in desacyl ghrelin levels between patients taking clozapine and the control group (272.09 ± 137.96 vs 259.62 ± 140.91 pg/mL, z = 0.17, P = 0.87). In the clozapine group, there were no differences between men and women for ghrelin levels (246.66 ± 123.17 vs 295.39 ± 151.77 pg/mL, z = -0.98, P = 0.32). In the clozapine group, fasting serum levels of ghrelin negatively correlated with waist-to-hip ratio (WHR) (r = -0.45, P = 0.03) and ionized calcium (r = -0.45, P = 0.03). Levels of ghrelin were lower in patients with WHR above World Health Organization-defined cut-off points (246.84 ± 114.34 [Q1 = 152.18, Q2 = 220.92, Q3 = 327.85] vs 400.30 ± 123.36 [Q1 = 283.73, Q2 = 414.03, Q3 = 485.8] pg/mL, z = 2.52, P = 0.01). In the clozapine group, there were no correlation with age, height, weight, body mass index, abdominal circumference, waist circumference, hip circumference, WHR, blood pressure, total cholesterol, high-density lipoproteins, low-density lipoproteins, triglycerides, uric acid, homocysteine, glucose, insulin, clozapine dose, duration of treatment with antipsychotics, duration of treatment with clozapine, total fat, target fat, basal metabolic rate, target weight, lean weight, body water, homoeostasis model assessment of insulin resistance (HOMA) 1-IR, HOMA2-IR and quantitative insulin sensitivity check index. CONCLUSION: Based on our results, we cannot conclude that treatment with clozapine affects levels of desacyl ghrelin. Also, in our study population we did not confirm previously described associations between desacyl ghrelin and various metabolic parameters.