Serum proteins mediate depression's association with dementia

INFLAMMATION's cognitive impact revealed by a novel "Line of Identity" approach

IMPORTANCE

Dementia is an "overdetermined" syndrome. Few individuals are demented by any single biomarker, while several may independently explain small fractions of dementia severity. It may be advantageous to identify individuals afflicted by a specific biomarker to guide individualized treatment.

OBJECTIVE

We aim to validate a psychometric classifier to identify persons adversely impacted by inflammation and replicate it in a second cohort.

DESIGN

Secondary analyses of data collected by the Texas Alzheimer's Research and Care Consortium (TARCC) (N = 3497) and the Alzheimer's Disease Neuroimaging Initiative (ADNI) (N = 1737).

SETTING

Two large, well-characterized multi-center convenience samples.

PARTICIPANTS

Volunteers with normal cognition (NC), Mild Cognitive Impairment (MCI) or clinical "Alzheimer's Disease (AD)".

EXPOSURE

Participants were assigned to "Afflicted" or "Resilient" classes on the basis of a psychometric classifier derived by confirmatory factor analysis.

MAIN OUTCOME(S) AND MEASURE(S)

The groups were contrasted on multiple assessments and biomarkers. The groups were also contrasted regarding 4-year prospective conversions to "AD" from non-demented baseline diagnoses (controls and MCI). The Afflicted groups were predicted to have adverse levels of inflammation-related blood-based biomarkers, greater dementia severity and greater risk of prospective conversion.

RESULTS

In ADNI /plasma, 47.1% of subjects were assigned to the Afflicted class. 44.6% of TARCC's subjects were afflicted, 49.5% of non-Hispanic Whites (NHW) and 37.2% of Mexican Americans (MA). There was greater dementia severity in the Afflicted class [by ANOVA: ADNI /F(1) = 686.99, p <0.001; TARCC /F(1) = 1544.01, p <0.001]. "INFLAMMATION" factor composite scores were significantly higher (adverse) in Afflicted subjects [by ANOVA in ADNI /plasma F(1) = 1642.64, p <0.001 and in TARCC /serum F(1) = 3059.96, p <0.001]. Afflicted cases were more likely to convert to AD in the next four years [by Cox's F, ADNI /plasma: F (252, 268) = 3.74 p < 0.001; TARCC /serum: F (160, 134) = 3.03, p < 0.001 (in TARCC's entire sample), F (110, 90) = 4.92, p <0.001 in NHW, and F(50, 44) = 2.13, p = 0.006 in MA]. The proportions converting were similar among afflicted NHW in both cohorts /biofluids but MA exhibited a lower risk (7% in TARCC /serum at 48 months).

CONCLUSIONS AND RELEVANCE

Our inflammation-specific psychometric classifier selects individuals with pre-specified biomarker profiles and predicts conversion to "AD" across cohorts, biofluids, and ethnicities. This algorithm might be applied to any dementia-related biomarker making the psychometric estimation of individual biomarker effects feasible without biomarker assessment. Our approach also distinguishes individuals resilient to individual biomarker effects allowing for more accurate prediction and precision intervention.

Multiple Adipokines Predict Dementia Severity as Measured by δ: Replication Across Biofluids and Cohorts

BACKGROUND

We have explored dementia's blood-based protein biomarkers in the Texas Alzheimer's Research and Care Consortium (TARCC) study. Among them are adipokines, i.e., proteins secreted by adipose tissue some of which have been associated with cognitive impairment.

OBJECTIVE

To associate adipokines with dementia severity and replicate their association across cohorts and biofluids (serum /plasma).

METHODS

We used eight rationally chosen blood-based protein biomarkers as indicators of a latent variable, i.e., "Adipokines". We then associated that construct with dementia severity as measured by the latent dementia-specific phenotype "δ" in structural equation models (SEM). Significant factor loadings and Adipokines' association with δ were replicated across biofluids in the Alzheimer's Disease Neuroimaging Initiative (ADNI).

RESULTS

Eight adipokine proteins loaded significantly on the Adipokines construct. Adipokines measured in plasma (ADNI) or serum (TARCC) explained 24 and 70% of δ's variance, respectively. An Adipokine composite score, derived from the latent variables, rose significantly across clinical diagnoses and achieved high areas under the receiver operating characteristic curve (ROC/AUC) for discrimination of Alzheimer's disease from normal controls (NC) or cases of mild cognitive impairment (MCI) and between NC and MCI.

CONCLUSION

These results again suggest that SEM can be used to create latent biomarker classifiers that replicate across samples and biofluids, and that a substantial fraction of dementia's variance is attributable to peripheral blood-based protein levels via the patterns codified in those latent constructs.

Apathy as a Predictor of Conversion from Mild Cognitive Impairment to Alzheimer's Disease: A Texas Alzheimer's Research and Care Consortium (TARCC) Cohort-Based Analysis

BACKGROUND

Apathy is among the neuropsychiatric symptoms frequently observed in people with cognitive impairment. It has been postulated to be a potential predictor of conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD).

OBJECTIVE

To detect conversion rates from MCI to AD, and to determine the effect of apathy on the progression to AD in patients with MCI enrolled in the Texas Alzheimer's Research and Care Consortium (TARCC) cohort.

METHODS

Apathy was determined by a positive response to the respective item in the Neuropsychiatric Inventory -Questionnaire (NPI-Q) completed by family members or caregivers. The final dataset included 2,897 observations from 1,092 individuals with MCI at the baseline. Kaplan-Meier survival curves were estimated to provide indices of the probability of conversion to AD over time across all individuals as well as between those with and without apathy. Cox proportional hazards regression measured the hazard associated with apathy and several other predictors of interest.

RESULTS

Over a period of 8.21 years, 17.3% of individuals had conversion from MCI to AD (n = 190 of 1,092 total individuals) across observations. The median time-to-conversion across all participants was 6.41 years. Comparing individuals with apathy (n = 158) versus without apathy (n = 934), 36.1% and 14.2% had conversion to AD, respectively. The median time-to-conversion was 3.79 years for individuals with apathy and 6.83 years for individuals without apathy. Cox proportional hazards regression found significant effects of several predictors, including apathy, on time-to-conversion. Age and cognitive performance were found to moderate the relationship between apathy and time-to-conversion.

CONCLUSIONS

Apathy is associated with progression from MCI to AD, suggesting that it might improve risk prediction and aid targeted intervention delivery.

Cerebrospinal Fluid Proteome Alterations Associated with Neuropsychiatric Symptoms in Cognitive Decline and Alzheimer's Disease

Although neuropsychiatric symptoms (NPS) are common and severely affect older people with cognitive decline, little is known about their underlying molecular mechanisms and relationships with Alzheimer’s disease (AD). The aim of this study was to identify and characterize cerebrospinal fluid (CSF) proteome alterations related to NPS. In a longitudinally followed-up cohort of subjects with normal cognition and patients with cognitive impairment (MCI and mild dementia) from a memory clinic setting, we quantified a panel of 790 proteins in CSF using an untargeted shotgun proteomic workflow. Regression models and pathway enrichment analysis were used to investigate protein alterations related to NPS, and to explore relationships with AD pathology and cognitive decline at follow-up visits. Regression analysis selected 27 CSF proteins associated with NPS. These associations were independent of the presence of cerebral AD pathology (defined as CSF p-tau181/Aβ1−42 > 0.0779, center cutoff). Gene ontology enrichment showed abundance alterations of proteins related to cell adhesion, immune response, and lipid metabolism, among others, in relation to NPS. Out of the selected proteins, three were associated with accelerated cognitive decline at follow-up visits after controlling for possible confounders. Specific CSF proteome alterations underlying NPS may both represent pathophysiological processes independent from AD and accelerate clinical disease progression.

Increased serum resistin but not G-CSF levels are associated in the pathophysiology of major depressive disorder: Findings from a case-control study

Background

Many studies have predicted major depressive disorder (MDD) as the leading cause of global health by 2030 due to its high prevalence, disability, and illness. However, the actual pathophysiological mechanism behind depression is unknown. Scientists consider alterations in cytokines might be tools for understanding the pathogenesis and treatment of MDD. Several past studies on several inflammatory cytokine expressions in MDD reveal that an inflammatory process is activated, although the precise causes of that changes in cytokine levels are unclear. Therefore, we aimed to investigate resistin and G-CSF in MDD patients and controls to explore their role in the pathogenesis and development of depression.

Methods

We included 220 participants in this study. Among them, 108 MDD patients and 112 age-sex matched healthy control (HCs). We used DSM-5 to evaluate study participants. Also, we applied the Ham-D rating scale to assess the severity of patients. Serum resistin and G-CSF levels were measured using ELISA kits (BosterBio, USA).

Results

The present study observed increased serum resistin levels in MDD patients compared to HCs (13.82 ± 1.24ng/mL and 6.35 ± 0.51ng/mL, p <0.001). However, we did not find such changes for serum G-CSF levels between the groups. Ham-D scores showed a significant correlation with serum resistin levels but not G-CSF levels in the patient group. Furthermore, ROC analysis showed a fairly predictive performance of serum resistin levels in major depression (AUC = 0.746).

Conclusion

The present study findings suggest higher serum resistin levels are associated with the pathophysiology of MDD. This elevated serum resistin level may serve as an early risk assessment indicator for MDD. However, the role of serum G-CSF in the development of MDD is still unclear despite its neuroprotective and anti-inflammatory effects.

Transcriptomic profiling as biological markers of depression - A pilot study in unipolar and bipolar women

OBJECTIVES

A significant challenge in psychiatry is the differential diagnosis of depressive episodes in the course of mood disorders. Gene expression profiling may provide an opportunity for such distinguishment.

METHODS

We studied differentially expressed genes in women with a depressive episode in the course of unipolar depression (UD) (n = 24) and bipolar disorder types I (BDI) (n = 13) and II (BDII) (n = 19), and healthy controls (n = 15).

RESULTS

Different types of depression varied in the number and type of up or down-regulated genes. The pathway analysis showed: in UD, up-regulated rheumatoid arthritis pathway (including ITGB2, CXCL8, TEK, TLR4 genes), and down-regulated taste transduction pathway (TAS2R10, TAS2R46, TAS2R14, TAS2R43, TAS2R45, TAS2R19, TAS2R13, TAS2R20, GNG13); in BDI, eight down-regulated pathways: glutamatergic synapse, retrograde endocannabinoid signalling, axon guidance, calcium signalling, nicotine addiction, PI3K-Akt signalling, drug metabolism - cytochrome P450, and morphine addiction; in BDII, up-regulated osteoclast differentiation and Notch signalling pathway, and down-regulated type I diabetes mellitus pathway. Distinct expression markers analysis uncovered the unique for UD, up-regulated bladder cancer pathway (HBEGF and CXCL8 genes).

CONCLUSIONS

This pilot study suggests a probability of differentiating depression in the course of UD, BDI, and II, based on transcriptomic profiling.

Treatment-emergent and trajectory-based peripheral gene expression markers of antidepressant response

Identifying biomarkers of antidepressant response may advance personalized treatment of major depressive disorder (MDD). We aimed to identify longitudinal changes in gene expression associated with response to antidepressants in a sample of MDD patients treated with escitalopram. Patients (N = 153) from the CAN-BIND-1 cohort were treated for 8 weeks, and depressive symptoms were assessed using the Montgomery-Åsberg Depression Rating Scale at 0, 2, 4, 6, and 8 weeks. We identified three groups of patients according to response status: early responders (22.9%), later responders (32.0%), and nonresponders (45.1%). RNA sequencing was performed in blood obtained at weeks 0, 2, and 8. RNA expression was modeled using growth models, and differences in the longitudinal changes in expression according to response were investigated using multiple regression models. The expression of RNAs related to response was investigated in the brains of depressed individuals, as well as in neuronal cells in vitro. We identified four RNAs (CERCAM, DARS-AS1, FAM228B, HBEGF) whose change over time was independently associated with a response status. For all except HBEGF, responders showed higher expression over time, compared to nonresponders. While the change in all RNAs differentiated early responders from nonresponders, changes in DARS-AS1 and HBEGF also differentiated later responders from nonresponders. Additionally, HBEGF was downregulated in the brains of depressed individuals, and increased in response to escitalopram treatment in vitro. In conclusion, using longitudinal assessments of gene expression, we provide insights into biological processes involved in the intermediate stages of escitalopram response, highlighting several genes with potential utility as biomarkers of antidepressant response.

CCR5-Δ32 polymorphism: a possible protective factor for post-stroke depressive symptoms

BACKGROUND

A naturally occurring loss-of-function mutation in the gene for C-C chemokine receptor type 5 (CCR5-Δ32) has recently been reported as a protective factor in post-stroke motor and cognitive recovery. We sought to examine whether this mutation also prevented the development of depressive symptoms up to 2 years after a stroke.

METHODS

Participants were survivors of a first-ever mild to moderate ischemic stroke or transient ischemic attack from the TABASCO prospective study who underwent a 3 T MRI at baseline and were examined by a multiprofessional team 6, 12 and 24 months after the event, including an evaluation of depressive symptoms using the Geriatric Depression Scale.

RESULTS

CCR5-Δ32 status and a baseline depression evaluation were available for 435 patients. Compared with noncarriers, CCR5-Δ32 carriers (16.1%) had fewer depressive symptoms at admission (p = 0.035) and at 6 months (p < 0.001), 12 months (p < 0.001) and 24 months (p = 0.006) after the index event. This association remained significant at 6 and 12 months after adjustment for age, sex, education, antidepressant use, ethnicity and the presence of cortical infarcts. These findings were more robust in women. Compared to baseline, depressive symptoms in CCR5-Δ32 noncarriers tended to remain stable or grow worse over time, but in CCR5-Δ32 carriers, symptoms tended to improve.

LIMITATIONS

A limitation of this study was the exclusion of patients who had a severe stroke or who had pre-stroke depression.

CONCLUSION

Carriers of the CCR5-Δ32 allele had a lower tendency to develop depressive symptoms post-stroke, and this phenomenon was more prominent in women. These findings could have clinical implications; they suggest a mechanism-based treatment target for post-stroke depression. Drugs mimicking this loss-of-function mutation exist and could serve as a novel antidepressant therapy.

δ scores predict multiple neuropsychiatric symptoms

OBJECTIVES

Dementia severity is strongly related to Spearman's general intelligence factor "g", via the latent dementia phenotype "δ" and is distinct from domain-specific cognitive impairments arising from disease-specific regional pathologies. It is an empiric question whether behavioral and psychological symptoms of dementia (BPSD) are associated with δ or with domain-specific constructs.

METHODS

A recently developed δ homolog ("dDx") was tested as a predictor of 1 year prospective BPSD in n = 723 Mexican-American and non-Hispanic White participants in the Texas Alzheimer's Research and Care Consortium (TARCC). The informant-rated frequencies of 12 BPSD were rated by the neuropsychiatric inventory (NPI-Q). Baseline BPSD, demographic features, selected biomarkers, and treatment exposure to acetylcholinesterase inhibitors were used as covariates. Composite scores derived from orthogonal latent measures of domain-specific memory (MEM) and executive function (EF) were also tested as predictors.

RESULTS

"Functionally salient cognitive impairment (FSCI)" that is, categorical "dementia" as diagnosed by dDx was associated with increased prospective frequency of 11/12 BPSD, independently of baseline behavior and covariates. Age, depressive symptoms, and EF were associated with individual BPSD. MEM was not associated with any. Dementia severity, as measured by dDx, was also associated with a prospective increase in total NPI-Q scores.

CONCLUSION

δ is associated non-specifically with multiple BPSD. This suggests the existence of a dementia-specific behavioral profile, arising from insults to general intelligence, and unrelated to disease-specific regional pathology(ies).

δ-Related Biomarkers Attenuate Multiple Alzheimer's Disease Conversion Risks and Offer Targets for Intervention

BACKGROUND

We tested certain serum proteins' ability to mediate the effects of demographic variables on prospective 5-year conversion to clinical "Alzheimer's disease" from non-demented states (i.e. normal control and mild cognitive impairment). The proteins were rationally selected from previously published mediators of those same variables' (plural posessive) association with the latent variable "δ," a novel omnibus dementia severity metric.

METHODS

Each protein's attenuation of its risk factor's independent association with conversion was performed using logistic regression, adjusted for education, ethnicity, self-reported diabetes mellitus, and hypertension, among initially non-demented Mexican American and non-Hispanic white (N = 772) participants in the Texas Alzheimer's Research and Care Consortium.

RESULTS

A total of 70 (9.1%) non-demented participants at baseline converted to "Alzheimer's disease", with a mean follow-up of 5.4 years. Age >80 years (odds ratio = 3.1), 30-item Geriatric Depression Scale >10/30 (odds ratio = 2.3), female gender (odds ratio = 2.2), and the presence of an apolipoprotein E ε4 allele (odds ratio = 2.4) were independently associated with prospective conversion. These effects were fully attenuated by five serum proteins: age: insulin-like growth factor-binding protein 2 and epidermal growth factor receptor 1; depression: resistin; gender: thrombopoietin; and apolipoprotein E: C-reactive protein.

CONCLUSION

Clinical dementia arises from the sum of independent δ-related processes. This analysis provides proof of concept for the rational selection of antidementia targets and offers a foundation for precision antidementia therapy.

[Characteristic of innate and acquired immunity in adaptation disorders]

OBJECTIVE

To determine factors of innate and acquired immunity in adaptation disorders with a predominance of asthenic or anxiety-depressive syndrome.

MATERIAL AND METHODS

Twenty-five patients with ICD-10 diagnosis of «Adaptation Disorders» (F43.2), including 9 with asthenic syndrome and 16 with anxiety-depressive syndrome, were examined. The control group consisted of 23 healthy individuals. The relative number of lymphocyte phenotypes was determined by flow cytometry; the concentration of IgM, IgG, IgA, aAB to S100b and MBP - by ELISA; CIC level - by the method of selective precipitation with PEG-6000; phagocytic activity of neutrophils by a test system with melamine-formaldehyde latex; activities of leukocyte elastase (LE) and α1-proteinase inhibitor (α1-PI) by a spectrophotometric method.

RESULTS

There were significant changes in the parameters of acquired immunity in the group with asthenic syndrome and those of innate immunity in the group with anxiety-depressive syndrome. An increase in α1-PI activity, in the total number of significant correlations between different immunological parameters, in the involvement of α1-PI in integration of acquired and innate immunity were observed in the anxiety-depressive group compared with the asthenic group.

CONCLUSIONS

The peculiarities of stress response in patients with leading anxiety-depressive syndrome are the high activity of α1-PI, which, along with the strengthening of correlation intersystem associations and the involvement of this protein in the integration of acquired and innate immunity, allows us to consider α1-PI as a criterion that improves the accuracy of diagnosis of the nature of the course of adaptation disorders.

Blood-based protein predictors of dementia severity as measured by δ: Replication across biofluids and cohorts

INTRODUCTION

Dementia severity can be empirically described by the latent dementia phenotype "δ" and its various composite "homologs". We have explored δ's blood-based protein biomarkers in the Texas Alzheimer's Research and Care Consortium (TARCC) study. However, it would be convenient to replicate those associations in the Alzheimer's Disease Neuroimaging Initiative (ADNI). To this end, we recently engineered a δ homolog from observed cognitive performance measures common to both projects (i.e., "dT2A").

METHODS

We used nine rationally chosen peripheral blood-based protein biomarkers as indicators of a latent variable "INFLAMMATION". We then associated that construct with dT2A in structural equation models adjusted for age, gender, depressive symptoms, and apolipoprotein E (APOE) ε4 allelic burden. Significant factor loadings and INFLAMMATION's association with dT2A were confirmed in random splits of TARCC's relatively large sample, and across biofluids in the ADNI.

RESULTS

Nine proteins measured in serum (TARCC) or plasma (ADNI) explained ≅10% of dT2A's variance in both samples, independently of age, APOE, education, and gender. All loaded significantly on INFLAMMATION, and positively or negatively, depending on their known roles are PRO- or ANTI-inflammatory proteins, respectively. The parameters of interest were confirmed across random 50% splits of the TARCC's sample, and replicated across biofluids in the ADNI.

DISCUSSION

These results suggest that SEM can be used to replicate biomarker findings across samples and biofluids, and that a substantial fraction of dementia's variance is attributable to peripheral blood-based protein levels.

Blood-based protein mediators of senility with replications across biofluids and cohorts

Dementia severity can be quantitatively described by the latent dementia phenotype 'δ' and its various composite 'homologues'. We have explored δ's blood-based protein biomarkers in the Texas Alzheimer's Research and Care Consortium. However, it would be convenient to replicate them in the Alzheimer's Disease Neuroimaging Initiative. To that end, we have engineered a δ homologue from the observed cognitive performance measures common to both projects [i.e. 'd:Texas Alzheimer's Research and Care Consortium to Alzheimer's Disease Neuroimaging Initiative' (dT2A)]. In this analysis, we confirm 13/22 serum proteins as partial mediators of age's effect on dementia severity as measured by dT2A in the Texas Alzheimer's Research and Care Consortium and then replicate 4/13 in the Alzheimer's Disease Neuroimaging Initiative's plasma data. The replicated mediators of age-specific effects on dementia severity are adiponectin, follicle-stimulating hormone, pancreatic polypeptide and resistin. In their aggregate, the 13 confirmed age-specific mediators suggest that 'cognitive frailty' pays a role in dementia severity as measured by δ. We provide both discriminant and concordant support for that hypothesis. Weight, calculated low-density lipoprotein and body mass index are partial mediators of age's effect in the Texas Alzheimer's Research and Care Consortium. Biomarkers related to other disease processes (e.g. cerebrospinal fluid Alzheimer's disease-specific biomarkers in the Alzheimer's Disease Neuroimaging Initiative) are not. It now appears that dementia severity is the sum of multiple independent processes impacting δ. Each may have a unique set of mediating biomarkers. Age's unique effect appears to be at least partially mediated through proteins related to frailty. Age-specific mediation effects can be replicated across cohorts and biofluids. These proteins may offer targets for the remediation of age-specific cognitive decline (aka 'senility'), help distinguish it from other determinants of dementia severity and/or provide clues to the biology of Aging Proper.

Selection for depression-specific dementia cases with replication in two cohorts

The latent variable "δ" (for "dementia") provides an etiologically "agnostic" omnibus dementia severity metric capable of recognizing the dementing potential of any condition. Depressive symptoms are independent predictors of δ and are thereby implicated as "dementing". Serum resistin levels partially mediate the association between depressive symptoms and δ. We use a novel "off-diagonal" CHI SQ algorithm to demonstrate our ability to select individuals demented solely by depression's effect in both the Texas Alzheimer's Research and Care Consortium (TARCC) (N ≌ 3,500), and the Alzheimer's Disease Neuroimaging Initiative (ADNI (N ≌ 1,750), and demonstrate the higher resistin levels of such cases in TARCC. This approach can be adapted to any δ-related dementia risk factor or biomarker and used identify individuals who might revert back to non-demented states after its successful treatment.

Affective problems and decline in cognitive state in older adults: a systematic review and meta-analysis

Evidence suggests that affective problems, such as depression and anxiety, increase risk for late-life dementia. However, the extent to which affective problems influence cognitive decline, even many years prior to clinical diagnosis of dementia, is not clear. The present study systematically reviews and synthesises the evidence for the association between affective problems and decline in cognitive state (i.e., decline in non-specific cognitive function) in older adults. An electronic search of PubMed, PsycInfo, Cochrane, and ScienceDirect was conducted to identify studies of the association between depression and anxiety separately and decline in cognitive state. Key inclusion criteria were prospective, longitudinal designs with a minimum follow-up period of 1 year. Data extraction and methodological quality assessment using the STROBE checklist were conducted independently by two raters. A total of 34 studies (n = 71 244) met eligibility criteria, with 32 studies measuring depression (n = 68 793), and five measuring anxiety (n = 4698). A multi-level meta-analysis revealed that depression assessed as a binary predictor (OR 1.36, 95% CI 1.05-1.76, p = 0.02) or a continuous predictor (B = -0.008, 95% CI -0.015 to -0.002, p = 0.012; OR 0.992, 95% CI 0.985-0.998) was significantly associated with decline in cognitive state. The number of anxiety studies was insufficient for meta-analysis, and they are described in a narrative review. Results of the present study improve current understanding of the temporal nature of the association between affective problems and decline in cognitive state. They also suggest that cognitive function may need to be monitored closely in individuals with affective disorders, as these individuals may be at particular risk of greater cognitive decline.

A δ Homolog for Dementia Case Finding with Replication in the Alzheimer's Disease Neuroimaging Initiative

Dementia can be empirically described by the latent dementia phenotype "δ" and its various composite "homologs". We have explored δ's blood-based protein biomarkers in the Texas Alzheimer's Research and Care Consortium (TARCC) study. However, it would be convenient to replicate those associations in the Alzheimer's Disease Neuroimaging Initiative (ADNI). To this end, we have engineered a δ homolog from observed cognitive performance measures common to both projects. Our findings were replicated in randomly selected 50% splits of TARCC data (Group 1, N = 1,747; Group 2, N = 1,755), and then independently in ADNI (N = 1,737). The new δ homolog, i.e., "dT2A" (d-TARCC to ADNI), fit the data of both studies well, and was strongly correlated with dementia severity, as rated by the Clinical Dementia Rating Scale "sum of boxes" (TARCC: r = 0.99, p < 0.001; ADNI: r = 0.96, p < 0.001). dT2A achieved an area under the receiver operating characteristic curve of 0.981 (0.976-0.985) for the discrimination of Alzheimer's disease from normal controls in TARCC, and 0.988 (0.983-0.993) in ADNI. dT2A is the 12th δ homolog published to date, and opens the door to independent replications across these and similar studies.

Neurobiological parameters in quantitative prediction of treatment outcome in schizophrenic patients

The aim of the study was to reveal the set of neurobiological parameters informative for individual quantitative prediction of therapeutic response in schizophrenic patients. Correlation and regression analyses of quantitative clinical scores (by Positive And Negative Syndromes Scale - PANSS), together with background EEG spectral power values and four immunological parameters: enzymatic activity of leukocyte elastase and of alpha-1 proteinase inhibitor, as well as serum levels of autoantibodies to common myelin protein and to nerve growth factor, were performed in 50 patients (all females, aged 32.9±10.8 years) with hallucinatory-delusional disorders in the frames of attack-like paranoid schizophrenia. Background neurobiological data obtained before the beginning of syndrome based treatment course (at visit 1) were matched with PANSS clinical scores of the same patients after treatment course at the stage of remission establishment (at visit 2). The multiple linear regression equations were created which contained only 3 to 4 (from initial 80) background EEG parameters and one of four immunological parameters. These mathematical models allowed prediction from 65% to 76% of PANSS scores variance after treatment course (at visit 2). The data obtained may be used for elaboration of methods of individual quantitative prediction of treatment outcome in schizophrenic patients.