Vascular Risk Predicts Plasma Amyloid ß 42/40 Through Cerebral Amyloid Burden in Apolipoprotein E ε4 Carriers.

BACKGROUND: Understanding the neurobiological underpinnings between established multimodal dementia risk factors and noninvasive blood-based biomarkers may lead to greater precision and earlier identification of older adults at risk of accelerated decline and dementia. We examined whether key vascular and genetic risk impact the association between cerebral amyloid burden and plasma aß (amyloid ß) 42/40 in nondemented older adults. METHODS: We used nondemented older adults from the UCD-ADRC (University of California, Davis-Alzheimer's Disease Research Center) study (n=96) and Alzheimer's Disease Neuroimaging Initiative (n=104). Alzheimer's Disease Neuroimaging Initiative was examined as confirmatory study cohort. We followed a cross-sectional design and examined linear regression followed by mediation analyses. Vascular risk score was obtained as the sum of hypertension, diabetes, hyperlipidemia, coronary artery disease, and cerebrovascular disease. Apolipoprotein E (APOE) ε4+ risk was genotyped, and plasma aß42 and aß40 were assayed. Cerebral amyloid burden was quantified using Florbetapir-PET scans. Baseline age was included as a covariate in all models. RESULTS: Vascular risk significantly predicted cerebral amyloid burden in Alzheimer's Disease Neuroimaging Initiative but not in the UCD-ADRC cohort. Cerebral amyloid burden was associated with plasma aß 42/40 in both cohorts. Higher vascular risk increased cerebral amyloid burden was indirectly associated with reduced plasma aß 42/40 in Alzheimer's Disease Neuroimaging Initiative but not in UCD-ADRC cohort. However, when stratified by APOE ε4+ risk, we consistently observed this indirect relationship only in APOE ε4+ carriers across both cohorts. CONCLUSIONS: Vascular risk is indirectly associated with the level of plasma aß 42/40 via cerebral amyloid burden only in APOE ε4+ carriers. Nondemented older adults with genetic vulnerability to dementia and accelerated decline may benefit from careful monitoring of vascular risk factors directly associated with cerebral amyloid burden and indirectly with plasma aß 42/40.

Plasma biomarkers predict cognitive trajectories in an ethnoracially and clinically diverse cohort: Mediation with hippocampal volume.

Introduction: We examine whether the association between key plasma biomarkers (amyloid ß [aß] 42/40, total tau (t-tau), neurofilament light [NfL]) and cognitive trajectories (executive function [EF] and episodic memory [EM]) is mediated through neurodegeneration. Methods: All participants were recruited from the University of California, Davis-Alzheimer's Disease Research Center (n = 473; baseline age range = 49-95 years, 60% women). We applied an accelerated longitudinal design to test latent growth models for EF and EM, and path and mediation analyses. Age was centered at 75 years, and all models were adjusted for sex, education, and ethnicity. Results: HV differentially mediated the association aß 42/40 and NfL on EF and EM level and change. Hippocampal volume (HV) did not mediate the association between t-tau and cognitive performance. Discussion: Neurodegeneration as represented with HV selectively mediates the association between key non-invasive plasma biomarkers and cognitive trajectories in an ethnoracially and clinically diverse community-based sample.

Differential Cognitive Decline in Alzheimer's Disease Is Predicted by Changes in Ventricular Size but Moderated by Apolipoprotein E and Pulse Pressure.

BACKGROUND: Differential cognitive trajectories in Alzheimer's disease (AD) may be predicted by biomarkers from multiple domains. OBJECTIVE: In a longitudinal sample of AD and AD-related dementias patients (n = 312), we tested whether 1) change in brain morphometry (ventricular enlargement) predicts differential cognitive trajectories, 2) further risk is contributed by genetic (Apolipoprotein E [APOE] ɛ4+) and vascular (pulse pressure [PP]) factors separately, and 3) the genetic + vascular risk moderates this pattern. METHODS: We applied a dynamic computational approach (parallel process models) to test both concurrent and change-related associations between predictor (ventricular size) and cognition (executive function [EF]/attention). We then tested these associations as stratified by APOE (ɛ4-/ɛ4+), PP (low/high), and APOE+ PP (low/intermediate/high) risk. RESULTS: First, concurrently, higher ventricular size predicted lower EF/attention performance and, longitudinally, increasing ventricular size predicted steeper EF/attention decline. Second, concurrently, higher ventricular size predicted lower EF/attention performance selectively in APOEɛ4+ carriers, and longitudinally, increasing ventricular size predicted steeper EF/attention decline selectively in the low PP group. Third, ventricular size and EF/attention associations were absent in the high APOE+ PP risk group both concurrently and longitudinally. CONCLUSION: As AD progresses, a threshold effect may be present in which ventricular enlargement in the context of exacerbated APOE+ PP risk does not produce further cognitive decline.

Brain atrophy trajectories predict differential functional performance in Alzheimer's disease: Moderations with apolipoprotein E and sex.

INTRODUCTION: We examine whether distinct brain atrophy patterns (using brain parenchymal fraction [BPF]) differentially predict functional performance and decline in Alzheimer's disease (AD), and are independently moderated by (1) a key AD genetic risk marker (apolipoprotein E [APOE]), (2) sex, and (3) high-risk group (women APOE ɛ4 carriers). METHODS: We used a 2-year longitudinal sample of AD patients (baseline N = 170; mean age = 71.3 [9.1] years) from the Sunnybrook Dementia Study. We applied latent class analysis, latent growth modeling, and path analysis. We aimed to replicate our findings (N = 184) in the Alzheimer's Disease Neuroimaging Initiative. RESULTS: We observed that high brain atrophy class predicted lower functional performance and steeper decline. This association was moderated by APOE, sex, and high-risk group. Baseline findings as moderated by APOE and high-risk group were replicated. DISCUSSION: Women APOE ɛ4 carriers may selectively be at a greater risk of functional impairment with higher brain atrophy.

A Multimodal Risk Network Predicts Executive Function Trajectories in Non-demented Aging.

Background: Multiple modalities of Alzheimer's disease (AD) risk factors may operate through interacting networks to predict differential cognitive trajectories in asymptomatic aging. We test such a network in a series of three analytic steps. First, we test independent associations between three risk scores (functional-health, lifestyle-reserve, and a combined multimodal risk score) and cognitive [executive function (EF)] trajectories. Second, we test whether all three associations are moderated by the most penetrant AD genetic risk [Apolipoprotein E (APOE) ε4+ allele]. Third, we test whether a non-APOE AD genetic risk score further moderates these APOE × multimodal risk score associations. Methods: We assembled a longitudinal data set (spanning a 40-year band of aging, 53-95 years) with non-demented older adults (baseline n = 602; Mage = 70.63(8.70) years; 66% female) from the Victoria Longitudinal Study (VLS). The measures included for each modifiable risk score were: (1) functional-health [pulse pressure (PP), grip strength, and body mass index], (2) lifestyle-reserve (physical, social, cognitive-integrative, cognitive-novel activities, and education), and (3) the combination of functional-health and lifestyle-reserve risk scores. Two AD genetic risk markers included (1) APOE and (2) a combined AD-genetic risk score (AD-GRS) comprised of three single nucleotide polymorphisms (SNPs; Clusterin[rs11136000], Complement receptor 1[rs6656401], Phosphatidylinositol binding clathrin assembly protein[rs3851179]). The analytics included confirmatory factor analysis (CFA), longitudinal invariance testing, and latent growth curve modeling. Structural path analyses were deployed to test and compare prediction models for EF performance and change. Results: First, separate analyses showed that higher functional-health risk scores, lifestyle-reserve risk scores, and the combined score, predicted poorer EF performance and steeper decline. Second, APOE and AD-GRS moderated the association between functional-health risk score and the combined risk score, on EF performance and change. Specifically, only older adults in the APOEε4- group showed steeper EF decline with high risk scores on both functional-health and combined risk score. Both associations were further magnified for adults with high AD-GRS. Conclusion: The present multimodal AD risk network approach incorporated both modifiable and genetic risk scores to predict EF trajectories. The results add an additional degree of precision to risk profile calculations for asymptomatic aging populations.

A multiomics approach to heterogeneity in Alzheimer's disease: focused review and roadmap.

Aetiological and clinical heterogeneity is increasingly recognized as a common characteristic of Alzheimer's disease and related dementias. This heterogeneity complicates diagnosis, treatment, and the design and testing of new drugs. An important line of research is discovery of multimodal biomarkers that will facilitate the targeting of subpopulations with homogeneous pathophysiological signatures. High-throughput 'omics' are unbiased data-driven techniques that probe the complex aetiology of Alzheimer's disease from multiple levels (e.g. network, cellular, and molecular) and thereby account for pathophysiological heterogeneity in clinical populations. This review focuses on data reduction analyses that identify complementary disease-relevant perturbations for three omics techniques: neuroimaging-based subtypes, metabolomics-derived metabolite panels, and genomics-related polygenic risk scores. Neuroimaging can track accrued neurodegeneration and other sources of network impairments, metabolomics provides a global small-molecule snapshot that is sensitive to ongoing pathological processes, and genomics characterizes relatively invariant genetic risk factors representing key pathways associated with Alzheimer's disease. Following this focused review, we present a roadmap for assembling these multiomics measurements into a diagnostic tool highly predictive of individual clinical trajectories, to further the goal of personalized medicine in Alzheimer's disease.

Alzheimer's Biomarkers From Multiple Modalities Selectively Discriminate Clinical Status: Relative Importance of Salivary Metabolomics Panels, Genetic, Lifestyle, Cognitive, Functional Health and Demographic Risk Markers.

Background: Among the neurodegenerative diseases of aging, sporadic Alzheimer's disease (AD) is the most prevalent and perhaps the most feared. With virtually no success at finding pharmaceutical therapeutics for altering progressive AD after diagnosis, research attention is increasingly directed at discovering biological and other markers that detect AD risk in the long asymptomatic phase. Both early detection and precision preclinical intervention require systematic investigation of multiple modalities and combinations of AD-related biomarkers and risk factors. We extend recent unbiased metabolomics research that produced a set of metabolite biomarker panels tailored to the discrimination of cognitively normal (CN), cognitively impaired and AD patients. Specifically, we compare the prediction importance of these panels with five other sets of modifiable and non-modifiable AD risk factors (genetic, lifestyle, cognitive, functional health and bio-demographic) in three clinical groups. Method: The three groups were: CN (n = 35), mild cognitive impairment (MCI; n = 25), and AD (n = 22). In a series of three pairwise comparisons, we used machine learning technology random forest analysis (RFA) to test relative predictive importance of up to 19 risk biomarkers from the six AD risk domains. Results: The three RFA multimodal prediction analyses produced significant discriminating risk factors. First, discriminating AD from CN was the AD metabolite panel and two cognitive markers. Second, discriminating AD from MCI was the AD/MCI metabolite panel and two cognitive markers. Third, discriminating MCI from CN was the MCI metabolite panel and seven markers from four other risk modalities: genetic, lifestyle, cognition and functional health. Conclusions: Salivary metabolomics biomarker panels, supplemented by other risk markers, were robust predictors of: (1) clinical differences in impairment and dementia and even; (2) subtle differences between CN and MCI. For the latter, the metabolite panel was supplemented by biomarkers that were both modifiable (e.g., functional) and non-modifiable (e.g., genetic). Comparing, integrating and identifying important multi-modal predictors may lead to novel combinations of complex risk profiles potentially indicative of neuropathological changes in asymptomatic or preclinical AD.

Metabolomics Analyses of Saliva Detect Novel Biomarkers of Alzheimer's Disease.

Using a non-invasive biofluid (saliva), we apply a powerful metabolomics workflow for unbiased biomarker discovery in Alzheimer's disease (AD). We profile and differentiate Cognitively Normal (CN), Mild Cognitive Impairment (MCI), and AD groups. The workflow involves differential chemical isotope labeling liquid chromatography mass spectrometry using dansylation derivatization for in-depth profiling of the amine/phenol submetabolome. The total sample (N = 109) was divided in to the Discovery Phase (DP) (n = 82; 35 CN, 25 MCI, 22 AD) and a provisional Validation Phase (VP) (n = 27; 10 CN, 10 MCI, 7 AD). In DP we detected 6,230 metabolites. Pairwise analyses confirmed biomarkers for AD versus CN (63), AD versus MCI (47), and MCI versus CN (2). We then determined the top discriminating biomarkers and diagnostic panels. A 3-metabolite panel distinguished AD from CN and MCI (DP and VP: Area Under the Curve [AUC] = 1.000). The MCI and CN groups were best discriminated with a 2-metabolite panel (DP: AUC = 0.779; VP: AUC = 0.889). In addition, using positively confirmed metabolites, we were able to distinguish AD from CN and MCI with good diagnostic performance (AUC > 0.8). Saliva is a promising biofluid for both unbiased and targeted AD biomarker discovery and mechanism detection. Given its wide availability and convenient accessibility, saliva is a biofluid that can promote diversification of global AD biomarker research.

Clinical dementia severity associated with ventricular size is differentially moderated by cognitive reserve in men and women.

BACKGROUND: Interindividual differences in cognitive reserve (CR) are associated with complex and dynamic clinical phenotypes observed in cognitive impairment and dementia. We tested whether (1) CR early in life (E-CR; measured by education and IQ), (2) CR later in life (L-CR; measured by occupation), and (3) CR panel (CR-P) with the additive effects of E-CR and L-CR, act as moderating factors between baseline ventricular size and clinical dementia severity at baseline and across 2 years. We further examined whether this moderation is differentially represented by sex. METHODS: We examined a longitudinal model using patients (N = 723; mean age = 70.8 ± 9.4 years; age range = 38-90 years; females = 374) from the Sunnybrook Dementia Study. The patients represented Alzheimer's disease (n = 439), mild cognitive impairment (n = 77), vascular cognitive impairment (n = 52), Lewy body disease (n = 30), and frontotemporal dementia (n = 125). Statistical analyses included (1) latent growth modeling to determine how clinical dementia severity changes over 2 years (measured by performance on the Dementia Rating Scale), (2) confirmatory factor analysis to establish a baseline E-CR factor, and (3) path analysis to predict dementia severity. Baseline age (continuous) and Apolipoprotein E status (ɛ4-/ɛ4+) were included as covariates. RESULTS: The association between higher baseline ventricular size and dementia severity was moderated by (1) E-CR and L-CR and (2) CR-P. This association was differentially represented in men and women. Specifically, men in only the low CR-P had higher baseline clinical dementia severity with larger baseline ventricular size. However, women in the low CR-P showed the (1) highest baseline dementia severity and (2) fastest 2-year decline with larger baseline ventricular size. CONCLUSIONS: Clinical dementia severity associated with ventricular size may be (1) selectively moderated by complex and additive CR networks and (2) differentially represented by sex. TRIALS REGISTRATION: ClinicalTrials.gov, NCT01800214 . Registered on 27 February 2013.

A Network of Genetic Effects on Non-Demented Cognitive Aging: Alzheimer's Genetic Risk (CLU + CR1 + PICALM) Intensifies Cognitive Aging Genetic Risk (COMT + BDNF) Selectively for APOEɛ4 Carriers.

BACKGROUND: Trajectories of complex neurocognitive phenotypes in preclinical aging may be produced differentially through selective and interactive combinations of genetic risk. OBJECTIVE: We organize three possible combinations into a "network" of genetic risk indices derived from polymorphisms associated with normal and impaired cognitive aging, as well as Alzheimer's disease (AD). Specifically, we assemble and examine three genetic clusters relevant to non-demented cognitive trajectories: 1) Apolipoprotein E (APOE), 2) a Cognitive Aging Genetic Risk Score (CA-GRS; Catechol-O-methyltransferase + Brain-derived neurotrophic factor), and 3) an AD-Genetic Risk Score (AD-GRS; Clusterin + Complement receptor 1 + Phosphatidylinositol-binding clathrin assembly protein). METHOD: We use an accelerated longitudinal design (n = 634; age range = 55-95 years) to test whether AD-GRS (low versus high) moderates the effect of increasing CA-GRS risk on executive function (EF) performance and change as stratified by APOE status (ɛ4+ versus ɛ4-). RESULTS: APOEɛ4 carriers with high AD-GRS had poorer EF performance at the centering age (75 years) and steeper 9-year decline with increasing CA-GRS but this association was not present in APOEɛ4 carriers with low AD-GRS. CONCLUSIONS: APOEɛ4 carriers with high AD-GRS are at elevated risk of cognitive decline when they also possess higher CA-GRS risk. Genetic risk from both common cognitive aging and AD-related indices may interact in intensification networks to differentially predict (1) level and trajectories of EF decline and (2) potential selective vulnerability for transitions into impairment and dementia.

Profiling novel metabolic biomarkers for Parkinson's disease using in-depth metabolomic analysis.

OBJECTIVE: To profile the amine/phenol submetabolome to determine potential metabolite biomarkers associated with Parkinson's disease (PD) and PD with incipient dementia. METHODS: At baseline of a 3-wave (18-month intervals) longitudinal study, serum samples were collected from 42 healthy controls and 43 PD patients. By wave 3 (year 3), 16 PD patients were diagnosed with dementia and were classified as PD with incipient dementia at baseline. Metabolomic profiling using dansylation isotope labeling liquid chromatography mass spectrometry was conducted to compare controls with the full PD, PD with no dementia, and PD with incipient dementia groups. RESULTS: Metabolomic analyses detected 719 common metabolites in 80% of the samples. Some were significantly altered in pairwise comparison of different groups (fold change of >1.2 or <0.83 with q < 0.05). We discriminated PD and controls by using a 5-metabolite panel, vanillic acid, 3-hydroxykynurenine, isoleucyl-alanine, 5-acetylamino-6-amino-3-methyluracil, and theophylline. The receiver operating characteristic curve produced an area-under-the-curve value of 0.955 with 87.5% sensitivity and 93.0% specificity. In comparing PD with no dementia with PD with incipient dementia, we used an 8-metabolite panel, His-Asn-Asp-Ser, 3,4-dihydroxyphenylacetone, desaminotyrosine, hydroxy-isoleucine, alanyl-alanine, putrescine [-2H], purine [+O] and its riboside. This produced an area-under-the-curve value of 0.862 with 80.0% sensitivity and 77.0% specificity. CONCLUSIONS: The significantly altered metabolites can be used to differentiate (1) PD patients from healthy controls with high accuracy and (2) the stable PD with no dementia group from those with incipient dementia. Following further validation in larger cohorts, these metabolites could be used for both discrimination and establishing prognosis in PD. © 2017 International Parkinson and Movement Disorder Society.

Executive function performance and change in aging is predicted by apolipoprotein E, intensified by catechol-O-methyltransferase and brain-derived neurotrophic factor, and moderated by age and lifestyle.

Recent studies have reported several genetic, health, and aging interaction effects in predicting cognitive performance and change. We used an accelerated longitudinal design to examine interactions among genetic, lifestyle, and aging for executive function (EF) in non-demented older adults (n = 634; age range = 53-95 years). The polymorphisms were apolipoprotein E (APOE), catechol-O-methyltransferase (COMT), and brain-derived neurotrophic factor (BDNF). We tested (1) independent and additive effects of APOE, COMT, and BDNF and (2) APOE effect modification for COMT + BDNF, on EF performance and 9-year change as separated by age and lifestyle activities. First, APOE ε4+ carriers had poorer EF performance and steeper 9-year decline. Second, APOE ε4+ carriers with (1) BDNF Met/Met genotype and (2) increasing allelic risk in the COMT + BDNF risk panel had poorer EF performance; these effects were moderated by lifestyle activities (composite of everyday social, physical, and cognitive activities). Examining APOE effect modification for COMT + BDNF risk panel effects with other moderating factors may help identify complex neurobiological and genetic underpinnings of polygenic phenotypes such as EF in aging.

Risk-reducing Apolipoprotein E and Clusterin genotypes protect against the consequences of poor vascular health on executive function performance and change in nondemented older adults.

We examined independent and cumulative effects of 2 Alzheimer's-related genetic polymorphisms, Apolipoprotein E (APOE) and Clusterin (CLU), in relation to the deleterious effects of poor vascular health (pulse pressure [PP]) on executive function (EF) performance and change in nondemented older adults. Using a sample (n = 593; age range = 53-95 years) from the Victoria Longitudinal Study, we applied latent growth modeling to test the effect of PP, as moderated by APOE and CLU, on an EF latent variable. EF was affected by higher levels of PP but differentially less so for carriers of low-risk alleles (APOE ɛ2+; CLU TT) than for moderate- or high-risk alleles (APOE ɛ2-; CLU C+). The cumulative genetic risk of APOE plus CLU provided similar moderation of PP level effects on EF. Future research may focus on how APOE and CLU might provide different but complementary contributions to predicting EF level and change. Vascular health risk in synergistic association with risk-related polymorphisms can elucidate the neurobiological underpinnings of cognitive trajectories in nondemented aging.

Apolipoprotein E and Clusterin can magnify effects of personality vulnerability on declarative memory performance in non-demented older adults.

OBJECTIVES: Recent research has linked psychological (personality) factors and specific genetic risk polymorphisms to performance on neurocognitive phenotypes. We examined whether episodic or semantic memory performance is associated with (a) three personality traits (i.e. neuroticism, extraversion, and openness to experience), (b) two neurodegenerative-related polymorphisms (i.e. Apolipoprotein E (APOE; rs7412; rs429358), Clusterin (CLU; rs11136000)), and (c) cross-domain risk interactions (magnification effects). METHODS: Linear growth models were examined to test independent associations between personality traits and declarative memory performance, and potential interaction effects with APOE and CLU genetic risk. Normal older adults (n = 282) with personality and genetic data from the Victoria Longitudinal Study were included at baseline and for up to 14 years of follow-up. RESULTS: First, we observed that higher openness to experience levels were associated with better episodic and semantic memory. Second, three significant gene × personality interactions were associated with poorer memory performance at baseline. These synergistic effects are: (a) APOE allelic risk (ε4+) carriers with lower openness to experience levels, (b) CLU (no risk: T/T) homozygotes with higher extraversion levels, and (c) CLU (no risk: T/T) homozygotes with lower neuroticism levels. CONCLUSIONS: Specific neurodegenerative-related genetic polymorphisms (i.e. APOE and CLU) moderate and magnify the risk contributed by selected personality trait levels (i.e. openness to experience, extraversion) on declarative memory performance in non-demented aging. Future research could target interactions of other personality traits and genetic polymorphisms in different clinical populations to predict other neurocognitive deficits or transitions to cognitive impairment and dementia.

Synergistic associations of catechol-O-methyltransferase and brain-derived neurotrophic factor with executive function in aging are selective and modified by apolipoprotein E.

Genetic polymorphisms of catechol-O-methyltransferase (COMT) and brain-derived neurotrophic factor (BDNF) have shown promising but inconsistent linkages with executive function (EF) in normal aging. We tested (1) independent contributions of COMT and BDNF risk; (2) potential magnification by risk-related interactions or additive effects with age; and (3) effect modification through stratification by apolipoprotein E (APOE) (risk: ε4+). Multiple linear regression models were applied with nondemented older adults (N = 634; range: 53-95 years) for an EF latent variable. No independent effects of BDNF or COMT on EF were observed. Additive (but not interactive) effects of COMT, BDNF, and age showed that older adults with a high-risk allelic combination performed differentially worse. Of 2 tested models of synergistic effects, the additive approach selectively supported a magnification hypothesis, which was qualified by the presence or the absence of APOE ε4.

Association of homocysteine with ventricular dilatation and brain atrophy in Parkinson's disease.

Parkinson's disease (PD) patients are treated with levodopa (L-dopa) to help stabilize their impaired motor abilities; however, L-dopa leads to increased homocysteine (Hcy) levels, which may have a deleterious effect on brain structure and function. The purpose of this study was to examine the impact of increased Hcy concentration on global brain atrophy as determined by magnetic resonance imaging in PD patients and controls. The effect of high Hcy level on ventricular dilatation (percentage of intracranial volume [%ICV]) and total tissue volume (%ICV) was examined at baseline and longitudinally at 36 months. Age, sex, education, and L-dopa duration (in PD patients) were included as covariates. Elevated Hcy levels correlated positively with ventricular dilatation (%ICV) in the whole sample (P = 0.004) and in the PD group (P = 0.008). At baseline, adults with a high Hcy level (>14 µmol/L) had higher ventricular volume (%ICV) than adults with a low Hcy level (≤ 14 µmol/L) in the whole sample (P = 0.006) and in the PD group (P = 0.03), which persisted over 36 months in both the whole sample (P = 0.004) and the PD group (P = 0.03). PD patients with high Hcy concentrations had a greater rate of ventricular enlargement (%ICV) over time compared with those with low Hcy concentration (P = 0.02). Elevated Hcy concentration was associated with increased ventricular dilatation (%ICV) in PD patients. A larger sample with a broader age range and longer follow-up is needed to establish the consequences of high Hcy level, including interactions with genetic and environmental risk factors, in PD.