Shraddha Sapkota

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

Parkinsons 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.

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

To profile the amine/phenol submetabolome to determine potential metabolite biomarkers associated with Parkinsons disease (PD) and PD with incipient dementia.

An Alzheimer's genetic risk composite, but not ApoE, intensifies diabetes-related neurocognitive slowing in nondemented older adults

Background:Risk factors (and their synergistic interactions) associated with Alzheimer’s disease (AD) may predict normal or preclinical deficits and decline. Although ApoE (rs429358, rs7412) is the gene most consistently linked with AD risk, genome-wide association studies have identified others, including CLU (rs11136000), CR1 (rs6656401), and PICALM (rs541458). Type 2 diabetes (T2D) is a risk factor for AD and for increased cognitive deficits in nondemented older adults. We examined if the effect of diabetes on neurocognitive speed performance (level) and longitudinal change was intensified by (a) genetic risk from each of the four variants independently or (b) an AD Genetic Risk Composite (AGRC) representing combined risk from all four variants. Methods: This longitudinal design included non-demented older adults (n1⁄4591, baseline M age1⁄469, age range 53–91, 68% women, 8% with T2D) followed over 9 years. Saliva was processed with standard procedures from Oragene-DNA Genotek. Genotyping was carried out using a PCR-RFLP strategy. The AGRC was created by summing allelic risk across the four specified genotypes: 01⁄4no risk, 11⁄4moderate risk, 21⁄4full risk and then grouped into low and high risk using median split (Mdn1⁄43.0). Statistical analyses included latent growth modeling testing independent and interactive effects on level (centering age1⁄475) and change using a confirmed neurocognitive speed latent variable consisting of choice reaction time, sentence verification, and lexical decision measures. Results:First, adults with T2D exhibited slower speed performance at age 75 than adults without T2D (b1⁄4.494, p1⁄4.007). Second, none of the genetic risk variants showed independent effects on speed performance or change. Third, interaction analyses (e.g., T2D x ApoE) showed no magnification of speed decrements. Fourth, intensification interaction analyses (T2D x AGRC) showed that adults in the high risk AGRC group with T2D exhibited significantly greater 9-year decline in speed (b1⁄4.048, p1⁄4.004). Finally, education and pulse pressure where significant covariates but did not alter the observed effects. Conclusions: Independently, as expected, diabetes was associated with cognitive slowing in nondemented aging. Only the AD Genetic Risk Composite, not ApoE or other variants, intensified the effects of T2D on neurocognitive speed in the form of exacerbated slowing over 9 years.

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.

NEUROPSYCHIATRIC SYMPTOMS PREDICT DAILY LIFE FUNCTIONALITY IN DEMENTIA PATIENTS: RESULTS FROM THE SUNNYBROOK DEMENTIA STUDY

where TMS power was increased up to 75% of stimulator output. Only 11 PDD (mean age 1⁄4 75.476 5.4) and 9 control participants (mean age 73.82 6 5.4) experienced phosphenes on 50% of trials (240 trials). Mixed effect analysis was implemented to investigate the effects of scalp region (anterior, posterior), pre-stimulus EEG power (within theta, low-alpha and high alpha bands), and participant group on phosphene experience. Results:In the anterior region, there was a significant effect of phosphene or no-phosphene condition on the low-alpha relative power (F(1,18)1⁄44.72, p1⁄40.043, h1⁄40.208). Both groups showed decreased low-alpha power before phosphene experience and low-alpha power was lower in PDD participants when compared to controls. When separating the PDD hallucinators from the non-hallucinators, a significant effect of phosphene condition was found in high-alpha band (F(1,17)1⁄4 7.79, p1⁄40.013, h1⁄40.314). The posterior high-alpha band power was lower in the PDD hallucinator subgroup at both phosphene/ no-phosphene conditions, but higher in the non-hallucinator subgroup when phosphenes were not experienced. Conclusions: Decreased neural excitability at low-alpha band within the visual cortex is a driver of phosphene experience in both control and PDD patients. However, our data suggests that patients that normally experience complex visual hallucinations are in constant state of decreased alpha power that may elicit this symptom.

TOWARD DISCOVERY OF MULTI-OMICS BIOTYPES OF ALZHEIMER’S DISEASE: A FOCUSED REVIEW AND PROPOSED ROAD MAP

functional magnetic resonance imaging (fMRI). The current study investigated differences in resting-state connectivity between AD patients with and without delusions.Methods:10 AD patients with delusions and 11 AD patients without delusions underwent fMRI scanning in a 3 Tesla scanner. The resting-state functional connectivity was assessed by parcellating the brain using a data-drivenmethod based on kmeans clustering, and measuring functional connectivity for frontal clusters, associated with cognitive control. The presence of delusions was evaluated using the Neuropsychiatric Inventory Questionnaire completed by an informant. Results:There were no significant differences in age, education, or global cognition as measured by the Montreal Cognitive Assessment (MoCA) between delusional and nondelusional groups. None of the delusional patients were on antipsychoticmedication. A single cluster of interest was analyzed, consisting of the superior medial frontal gyrus and the anterior cingulate. A twosample t-test found significantly increased connectivity (p<0.05, cluster size thresholded) between these regions of interest and the superior frontal gyrus in delusional compared to non-delusional patients. Conclusions:Our results suggest that aberrant resting-state connectivity between frontal regions may be related to the pathophysiology of delusions in Alzheimer’s disease. It is possible that altered frontal connectivity may be the brain trying to integrate disorganized neural processes, which can give rise to delusions[1]. The findings resemble resting-state abnormalities observed in patients with schizophrenia with delusions, with reports showing increased connectivity between the anterior cingulate gyrus (ACC) and medial frontal gyrus [2, 3].

NEUROIMAGING BIOMARKERS MODERATE THE ASSOCIATION BETWEEN DEMOGRAPHIC RISK AND DEMENTIA RATING SCALE ACROSS NEURODEGENERATIVE DISEASES: THE SUNNYBROOK DEMENTIA STUDY

Figure 1. Main and interaction effect of ADCI and LDCI on cortical atrophy. Random field theory was used to correct for multiple comparisons over the whole cortical mantle. Figure is shown at p<0.05, random field theory corrected. In the t-maps, the color indicates t-value of the statistical analysis. In the p-maps, blue areas are significant at the cluster level and red color corresponds to areas significant at the vertex level. Controlled for age, gender, education, and intracranial volume. Shraddha Sapkota, Joel Ramirez, Mario Masellis, Sandra E. Black, Sunnybrook Research Institute, Toronto, ON, Canada; Faculty ofMedicine, University of Toronto, Toronto, ON, Canada. Contact e-mail: shraddha. sapkota@sunnybrook.ca

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 APOE E4+ CARRIERS

Background: Performance and change in polygenic neurocognitive phenotypes during non-demented aging may be predicted and modified through selective interactions among genetic risk indices compiled with polymorphisms associated with both Alzheimer’s disease (AD) and typical brain aging. Suggestive evidence indicates that a cumulative Cognitive Aging Genetic Risk Score [CA-GRS; Catechol-O-methyltransferase (COMT, risk1⁄4Val+) + Brainderived neurotrophic factor (BDNF, risk1⁄4Met+)] predicts executive function (EF) performance but the effect may be modified by the leading AD genetic risk, Apolipoprotein E (APOE). Given the dynamic and inter-related mechanisms underlying transitions from non-demented aging to dementia, we examined three-way interactions among three genetic risk clusters: (1) APOE (risk1⁄4ε4+), (2) CA-GRS, and (3) a new AD Genetic Risk Score [AD-GRS; Clusterin (CLU, risk1⁄4C+) + Complement receptor 1 (CR1, risk1⁄4A+) + Phosphatidylinositol-binding clathrin assembly protein (PICALM, risk1⁄4T+)] in predicting EF performance and change. Methods: We used a three-wave (w9-year) longitudinal sample of non-demented older adults (baseline N1⁄4634; range1⁄453-95 years; Mage1⁄470.6) from the Victoria Longitudinal Study. We tested (1) the CA-GRS effect on EF, (2) moderation by AD-GRS on the CA-GRS model, and (3) these models as stratified by APOE. Targeted follow-up analyses were conducted to inform mechanism interpretations. We used confirmatory factor analysis (EF latent variable), latent growth curve modeling, and path analysis. Results: First, APOE modified the CA-GRS effect on EF in that higher genetic risk was associated with lower performance but only among APOE ε4+ carriers (b1⁄4-0.307; p1⁄4.013). Second, AD-GRS moderated the CA-GRS effect on EF as stratified by APOE. Specifically, only APOE ε4+ carriers with higher CAGRS and higher AD-GRS risk had lower EF performance at the centering age (75 years) (b1⁄4-0.297; p1⁄4.021) and borderline 9year decline (b1⁄4-0.011; p1⁄4.079). Third, in contrast, no moderation effect was observed for either (1) APOE ε4+ carriers with lower AD-GRS risk or (2) APOE non-risk carriers. Conclusions: In nondemented older adults, genetic risk from both common cognitive aging and AD-related indices may interact in intensification networks to differentially predict (1) level and trajectories of cognitive change and (2) potential vulnerability for transitions into dementia. Multivariate longitudinal research can aid in the detection of potential mechanisms underlying early differential changes.