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To assess the neurobiological substrate of initial cognitive decline in Parkinson's disease (PD) to inform patient management, clinical trial design, and development of treatments.We longitudinally assessed, up to 3 years, 423 newly diagnosed patients with idiopathic PD, untreated at baseline, from 33 international movement disorder centers. Study outcomes were four determinations of cognitive impairment or decline, and biomarker predictors were baseline dopamine transporter (DAT) single photon emission computed tomography (SPECT) scan, structural magnetic resonance imaging (MRI; volume and thickness), diffusion tensor imaging (mean diffusivity and fractional anisotropy), cerebrospinal fluid (CSF; amyloid beta [Aβ], tau and alpha synuclein), and 11 single nucleotide polymorphisms (SNPs) previously associated with PD cognition. Additionally, longitudinal structural MRI and DAT scan data were included. Univariate analyses were run initially, with false discovery rate = 0.2, to select biomarker variables for inclusion in multivariable longitudinal mixed-effect models.By year 3, cognitive impairment was diagnosed in 15-38% participants depending on the criteria applied. Biomarkers, some longitudinal, predicting cognitive impairment in multivariable models were: (1) dopamine deficiency (decreased caudate and putamen DAT availability); (2) diffuse, cortical decreased brain volume or thickness (frontal, temporal, parietal, and occipital lobe regions); (3) co-morbid Alzheimer's disease Aβ amyloid pathology (lower CSF Aβ 1-42); and (4) genes (COMT val/val and BDNF val/val genotypes).Cognitive impairment in PD increases in frequency 50-200% in the first several years of disease, and is independently predicted by biomarker changes related to nigrostriatal or cortical dopaminergic deficits, global atrophy due to possible widespread effects of neurodegenerative disease, co-morbid Alzheimer's disease plaque pathology, and genetic factors.

Abstract Blood-based biomarkers of Alzheimer disease (AD) may facilitate testing of historically under-represented groups. The Study of Race to Understand Alzheimer Biomarkers (SORTOUT-AB) is a multi-center longitudinal study to compare AD biomarkers in participants who identify their race as either Black or white. Plasma samples from 324 Black and 1,547 white participants underwent analysis with C2N Diagnostics’ PrecivityAD test for Aβ42 and Aβ40. Compared to white individuals, Black individuals had higher average plasma Aβ42/40 levels at baseline, consistent with a lower average level of amyloid pathology. Interestingly, this difference resulted from lower average levels of plasma Aβ40 in Black participants. Despite the differences, Black and white individuals had similar longitudinal rates of change in Aβ42/40, consistent with a similar rate of amyloid accumulation. Our results agree with multiple recent studies demonstrating a lower prevalence of amyloid pathology in Black individuals, and additionally suggest that amyloid accumulates consistently across both groups.

Abstract Objective Within Lewy body spectrum disorders (LBSD) with α‐synuclein pathology (αSyn), concomitant Alzheimer's disease (AD) pathology is common and is predictive of clinical outcomes, including cognitive impairment and decline. Plasma phosphorylated tau 181 (p‐tau181) is sensitive to AD neuropathologic change (ADNC) in clinical AD, and plasma glial fibrillary acidic protein (GFAP) is associated with the presence of β‐amyloid plaques. While these plasma biomarkers are well tested in clinical and pathological AD, their diagnostic and prognostic performance for concomitant AD in LBSD is unknown. Methods In autopsy‐confirmed αSyn‐positive LBSD, we tested how plasma p‐tau181 and GFAP differed across αSyn with concomitant ADNC (αSyn+AD; n = 19) and αSyn without AD (αSyn; n = 30). Severity of burden was scored on a semiquantitative scale for several pathologies (e.g., β‐amyloid and tau), and scores were averaged across sampled brainstem, limbic, and neocortical regions. Results Linear models showed that plasma GFAP was significantly higher in αSyn+AD compared to αSyn (β = 0.31, 95% CI = 0.065–0.56, and P = 0.015), after covarying for age at plasma, plasma‐to‐death interval, and sex; plasma p‐tau181 was not (P = 0.37). Next, linear models tested associations of AD pathological features with both plasma analytes, covarying for plasma‐to‐death, age at plasma, and sex. GFAP was significantly associated with brain β‐amyloid (β = 15, 95% CI = 6.1–25, and P = 0.0018) and tau burden (β = 12, 95% CI = 2.5–22, and P = 0.015); plasma p‐tau181 was not associated with either (both P > 0.34). Interpretation Findings indicate that plasma GFAP may be sensitive to concomitant AD pathology in LBSD, especially accumulation of β‐amyloid plaques.

Abstract Background Crucial to the success of clinical trials targeting early Alzheimer’s disease (AD) is recruiting participants who are more likely to progress over the course of the trials. We hypothesize that a combination of plasma and structural MRI biomarkers, which are less costly and non-invasive, is predictive of longitudinal progression measured by atrophy and cognitive decline in early AD, providing a practical alternative to PET or cerebrospinal fluid biomarkers. Methods Longitudinal T1-weighted MRI, cognitive (memory-related test scores and clinical dementia rating scale), and plasma measurements of 245 cognitively normal (CN) and 361 mild cognitive impairment (MCI) patients from ADNI were included. Subjects were further divided into β-amyloid positive/negative (Aβ+/Aβ−)] subgroups. Baseline plasma (p-tau181 and neurofilament light chain) and MRI-based structural medial temporal lobe subregional measurements and their association with longitudinal measures of atrophy and cognitive decline were tested using stepwise linear mixed effect modeling in CN and MCI, as well as separately in the Aβ+/Aβ− subgroups. Receiver operating characteristic (ROC) analyses were performed to investigate the discriminative power of each model in separating fast and slow progressors (first and last terciles) of each longitudinal measurement. Results A total of 245 CN (35.0% Aβ+) and 361 MCI (53.2% Aβ+) participants were included. In the CN and MCI groups, both baseline plasma and structural MRI biomarkers were included in most models. These relationships were maintained when limited to the Aβ+ and Aβ− subgroups, including Aβ− CN (normal aging). ROC analyses demonstrated reliable discriminative power in identifying fast from slow progressors in MCI [area under the curve (AUC): 0.78–0.93] and more modestly in CN (0.65–0.73). Conclusions The present data support the notion that plasma and MRI biomarkers, which are relatively easy to obtain, provide a prediction for the rate of future cognitive and neurodegenerative progression that may be particularly useful in clinical trial stratification and prognosis. Additionally, the effect in Aβ− CN indicates the potential use of these biomarkers in predicting a normal age-related decline.

Abstract Objective To determine if plasma tau phosphorylated at threonine 181 (p‐tau181) distinguishes pathology‐confirmed Alzheimer's disease (AD) from normal cognition (NC) adults, to test if p‐tau181 predicts cognitive and functional decline, and to validate findings in an external cohort. Methods Thirty‐one neuropathology‐confirmed AD cases, participants with clinical diagnoses of mild cognitive impairment (MCI, N = 91) or AD dementia (N = 64), and NC (N = 241) had plasma collected at study entry. The clinical diagnosis groups had annual cognitive (Mini‐Mental State Examination, MMSE) and functional (Clinical Dementia Rating Scale, CDR) measures. NC (N = 70), MCI (N = 75), and AD dementia (N = 50) cases from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were used as a validation cohort. Plasma p‐tau181 was measured using the Quanterix SiMoA HD‐X platform. Results Plasma p‐tau181 differentiated pathology‐confirmed AD from NC with negative amyloid PET scans with an AUC of 0.93. A cut point of 3.44 pg/mL (maximum Youden Index) had a sensitivity of 0.77, specificity of 0.96. p‐Tau181 values above the cut point were associated with the faster rate of decline in MMSE in AD dementia and MCI and a shorter time to a clinically significant functional decline in all groups. In a subset of MCI cases from ADNI, p‐tau181 values above the cut point associated with faster rate of decline in MMSE, and a shorter time to a clinically significant functional decline and conversion to dementia. Interpretation Plasma p‐tau181 differentiates AD pathology cases from NC with high accuracy. Higher levels of plasma p‐tau181 are associated with faster cognitive and functional decline.

Abstract The extracellular buildup of amyloid beta (Aβ) plaques in the brain is a hallmark of Alzheimer’s disease (AD). Detection of Aβ pathology is essential for AD diagnosis and for identifying and recruiting research participants for clinical trials evaluating disease-modifying therapies. Currently, AD diagnoses are usually made by clinical assessments, although detection of AD pathology with positron emission tomography (PET) scans or cerebrospinal fluid (CSF) analysis can be used by specialty clinics. These measures of Aβ aggregation, e.g. plaques, protofibrils, and oligomers, are medically invasive and often only available at specialized medical centers or not covered by medical insurance, and PET scans are costly. Therefore, a major goal in recent years has been to identify blood-based biomarkers that can accurately detect AD pathology with cost-effective, minimally invasive procedures. To assess the performance of plasma Aβ assays in predicting amyloid burden in the central nervous system (CNS), this review compares twenty-one different manuscripts that used measurements of 42 and 40 amino acid-long Aβ (Aβ42 and Aβ40) in plasma to predict CNS amyloid status. Methodologies that quantitate Aβ42 and 40 peptides in blood via immunoassay or immunoprecipitation-mass spectrometry (IP-MS) were considered, and their ability to distinguish participants with amyloidosis compared to amyloid PET and CSF Aβ measures as reference standards was evaluated. Recent studies indicate that some IP-MS assays perform well in accurately and precisely measuring Aβ and detecting brain amyloid aggregates.

Abstract Background Alzheimer’s disease (AD) shares risk factors with cardiovascular disease (CVD) and dysregulated cholesterol metabolism is a mechanism common to both diseases. Cholesterol efflux capacity (CEC) is an ex vivo metric of plasma high-density lipoprotein (HDL) function and inversely predicts incident CVD independently of other risk factors. Cholesterol pools in the central nervous system (CNS) are largely separate from those in blood, and CNS cholesterol excess may promote neurodegeneration. CEC of cerebrospinal fluid (CSF) may be a useful measure of CNS cholesterol trafficking. We hypothesized that subjects with AD and mild cognitive impairment (MCI) would have reduced CSF CEC compared with Cognitively Normal (CN) and that CSF apolipoproteins apoA-I, apoJ, and apoE might have associations with CSF CEC. Methods We retrieved CSF and same-day ethylenediaminetetraacetic acid (EDTA) plasma from 108 subjects (40 AD; 18 MCI; and 50 CN) from the Center for Neurodegenerative Disease Research biobank at the Perelman School of Medicine, University of Pennsylvania. For CSF CEC assays, we used N9 mouse microglial cells and SH-SY5Y human neuroblastoma cells, and the corresponding plasma assay used J774 cells. Cells were labeled with [3H]-cholesterol for 24 h, had ABCA1 expression upregulated for 6 h, were exposed to 33 μl of CSF, and then were incubated for 2.5 h. CEC was quantified as percent [3H]-cholesterol counts in medium of total counts medium+cells, normalized to a pool sample. ApoA-I, ApoJ, ApoE, and cholesterol were also measured in CSF. Results We found that CSF CEC was significantly lower in MCI compared with controls and was poorly correlated with plasma CEC. CSF levels of ApoJ/Clusterin were also significantly lower in MCI and were significantly associated with CSF CEC. While CSF ApoA-I was also associated with CSF CEC, CSF ApoE had no association with CSF CEC. CSF CEC is significantly and positively associated with CSF Aβ. Taken together, ApoJ/Clusterin may be an important determinant of CSF CEC, which in turn could mitigate risk of MCI and AD risk by promoting cellular efflux of cholesterol or other lipids. In contrast, CSF ApoE does not appear to play a role in determining CSF CEC.

Abstract Introduction Lumbar puncture (LP) to collect and examine cerebrospinal fluid (CSF) is an important option for the evaluation of Alzheimer's disease (AD) biomarkers but it is not routinely performed due to its invasiveness and link to adverse effects (AE). Methods We include all participants who received at least one LP in the Alzheimer's Disease Neuroimaging Initiative (ADNI) Study. For comparison between groups, two‐sample t‐tests for continuous, and Pearson's chi‐square test for categorical variables were performed. Results Two hundred twenty‐seven LP‐related AEs were reported by 172 participants after 1702 LPs (13.3%). The mean age of participants who reported at least one AE was 69.79 (standard deviation (SD) 6.3) versus none 72.44 (7.17) years (p

Abstract Objective Numerous investigators have theorized that postoperative changes in Alzheimer's disease neuropathology may underlie postoperative neurocognitive disorders. Thus, we determined the relationship between postoperative changes in cognition and cerebrospinal (CSF) tau, p‐tau‐181p, or Aβ levels after non‐cardiac, non‐neurologic surgery in older adults. Methods Participants underwent cognitive testing before and 6 weeks after surgery, and lumbar punctures before, 24 h after, and 6 weeks after surgery. Cognitive scores were combined via factor analysis into an overall cognitive index. In total, 110 patients returned for 6‐week postoperative testing and were included in the analysis. Results There was no significant change from before to 24 h or 6 weeks following surgery in CSF tau (median [median absolute deviation] change before to 24 h: 0.00 [4.36] pg/mL, p = 0.853; change before to 6 weeks: −1.21 [3.98] pg/mL, p = 0.827). There were also no significant changes in CSF p‐tau‐181p or Aβ over this period. There was no change in cognitive index (mean [95% CI] 0.040 [−0.018, 0.098], p = 0.175) from before to 6 weeks after surgery, although there were postoperative declines in verbal memory (−0.346 [−0.523, −0.170], p = 0.003) and improvements in executive function (0.394, [0.310, 0.479], p 0.05 for each). Interpretation Neurocognitive changes after non‐cardiac, non‐neurologic surgery in the majority of cognitively healthy, community‐dwelling older adults are unlikely to be related to postoperative changes in AD neuropathology (as assessed by CSF Aβ, tau or p‐tau‐181p levels or the p‐tau‐181p/Aβ or tau/Aβ ratios). Trial Registration: clinicaltrials.gov (NCT01993836).

Abstract Background Alzheimer’s disease (AD) cerebrospinal fluid (CSF) biomarker cutoffs from immunoassays with low interlaboratory variability in diverse ethnic groups are necessary for their use in clinics and clinical trials. With lack of cutoffs from fully automated immunoassay platforms in diverse races, the aim of this study is to evaluate the clinical utility of CSF AD biomarkers from the Lumipulse fully automated immunoassay based on β-amyloid (Aβ) positron emission tomography (PET) status comparing with these from two manual immunoassays, in Koreans. Methods Among 331 Korean participants enrolled from a prospective, 3-year longitudinal observational study of the validation cohort of Korean Brain Aging Study for the Early Diagnosis and Prediction of AD, 139 (29 CN, 58 SCD, 29 MCI, and 23 AD) provided CSF and 271 underwent baseline amyloid PET (n = 128 with overlapping CSF and Aβ-PET, and 143 without CSFs). Three annual cognitive and neuropsychiatric function tests were conducted. Aβ42, Aβ40, total-tau, and phosphorylated-tau181 were measured by Lumipulse fully automated immunoassay and two manual immunoassays (INNO-BIA AlzBio3, INNOTEST). Clinical utility of CSF biomarker cutoffs, based on 128 participants with Aβ-PET, was evaluated. Results Cognitive and neuropsychological scores differed significantly among the groups, with descending performance among CN>SCD>MCI>AD. Biomarker levels among immunoassays were strongly intercorrelated. We determined the Aβ-PET status in a subgroup without CSF (n = 143), and then when we applied CSF biomarker cutoffs determined based on the Aβ-PET status, the CSF biomarkers (cutoffs of 642.1 pg/mL for Aβ42, 0.060 for Aβ42/Aβ40, 0.315 for t-tau/Aβ42, and 0.051 for p-tau/Aβ42, respectively) showed good agreement with Aβ-PET (overall AUC ranges of 0.840–0.898). Use of the Aβ-PET-based CSF cutoffs showed excellent diagnostic discrimination between AD and CN (Aβ42, Aβ42/Aβ40, t-tau/Aβ42, and p-tau/Aβ42) with overall AUC ranges of 0.876–0.952. During follow-up, participants with AD-like CSF signature determined by Aβ-PET-based cutoffs from Lumipulse showed rapid progression of cognitive decline in 139 subjects, after adjustment for potential confounders, compared with those with a normal CSF signature. Conclusion CSF AD biomarkers measured by different immunoassay platforms show strong intercorrelated agreement with Aβ-PET in Koreans. The Korean-specific Aβ-PET-based CSF biomarker cutoffs measured by the Lumipulse assay strongly predicts progression of cognitive decline. The clinical utility of CSF biomarkers from fully-automated immunoassay platforms should be evaluated in larger, more diverse cohorts.

Sex and the APOE ε4 genotype are important risk factors for late-onset Alzheimer’s disease. In the current study, the authors investigate how sex and APOE ε4 genotype modify the association between Alzheimer’s disease biomarkers and metabolites in serum.

Abstract Introduction Neuroimaging heterogeneity in dementia has been examined using single modalities. We evaluated the associations of magnetic resonance imaging (MRI) atrophy and flortaucipir positron emission tomography (PET) clusters across the Alzheimer's disease (AD) spectrum. Methods We included 496 Alzheimer's Disease Neuroimaging Initiative participants with brain MRI, flortaucipir PET scan, and amyloid beta biomarker measures obtained. We applied a novel robust collaborative clustering (RCC) approach on the MRI and flortaucipir PET scans. We derived indices for AD‐like (SPARE‐AD index) and brain age (SPARE‐BA) atrophy. Results We identified four tau (I–IV) and three atrophy clusters. Tau clusters were associated with the apolipoprotein E genotype. Atrophy clusters were associated with white matter hyperintensity volumes. Only the hippocampal sparing atrophy cluster showed a specific association with brain aging imaging index. Tau clusters presented stronger clinical associations than atrophy clusters. Tau and atrophy clusters were partially associated. Conclusions Each neuroimaging modality captured different aspects of brain aging, genetics, vascular changes, and neurodegeneration leading to individual multimodal phenotyping.

Background Recently, tau PET tracers have shown strong associations with clinical outcomes in individuals with cognitive impairment and cognitively unremarkable elderly individuals. flortaucipir PET scans to measure tau deposition in multiple brain areas as the disease progresses. This information needs to be summarized to evaluate disease severity and predict disease progression. We, therefore, sought to develop a machine learning-derived index, SPARE-Tau, which successfully detects pathology in the earliest disease stages and accurately predicts progression compared to a priori-based region of interest approaches (ROI). Methods 587 participants of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort had flortaucipir scans, structural MRI scans, and an Aβ biomarker test (CSF or florbetapir PET) performed on the same visit. We derived the SPARE-Tau index in a subset of 367 participants. We evaluated associations with clinical measures for CSF p-tau, SPARE-MRI, and flortaucipir PET indices (SPARE-Tau, meta-temporal, and average Braak ROIs). Bootstrapped multivariate adaptive regression splines linear regression analyzed the association between the biomarkers and baseline ADAS-Cog13 scores. Bootstrapped multivariate linear regression models evaluated associations with clinical diagnosis. Cox-hazards and mixed-effects models investigated clinical progression and longitudinal ADAS-Cog13 changes. The Aβ positive cognitively unremarkable participants, not included in the SPARE-Tau training, served as an independent validation group. Results Compared to CSF p-tau, meta-temporal, and averaged Braak tau PET ROIs, SPARE-Tau showed the strongest association with baseline ADAS-cog13 scores and diagnosis. SPARE-Tau also presented the strongest association with clinical progression in cognitively unremarkable participants and longitudinal ADAS-Cog13 changes. Results were confirmed in the Aβ+ cognitively unremarkable hold-out sample participants. CSF p-tau showed the weakest cross-sectional associations and longitudinal prediction. Discussion Flortaucipir indices showed the strongest clinical association among the studied biomarkers (flortaucipir, florbetapir, structural MRI, and CSF p-tau) and were predictive in the preclinical disease stages. Among the flortaucipir indices, the machine-learning derived SPARE-Tau index was the most sensitive clinical progression biomarker. The combination of different biomarker modalities better predicted cognitive performance.

The Lewy Body Dementia Association (LBDA) held a virtual event, the LBDA Biofluid/Tissue Biomarker Symposium, on January 25, 2021, to present advances in biomarkers for Lewy body dementia (LBD), which includes dementia with Lewy bodies (DLBs) and Parkinson's disease dementia (PDD). The meeting featured eight internationally known scientists from Europe and the United States and attracted over 200 scientists and physicians from academic centers, the National Institutes of Health, and the pharmaceutical industry. Methods for confirming and quantifying the presence of Lewy body and Alzheimer's pathology and novel biomarkers were discussed.

In this review, we provide an overview of the role of the insulin-like growth factor (IGF) signaling pathway in breast cancer and discuss its potential as a therapeutic target. The IGF pathway ligands, IGF-1 and IGF-2, and their receptors, primarily IGF-1R, are important for normal mammary gland biology, and dysregulation of their expression and function drives breast cancer risk and progression through activation of downstream signaling effectors, often in a subtype-dependent manner. The IGF signaling pathway has also been implicated in resistance to current therapeutic strategies, including ER and HER2 targeting drugs. Unfortunately, efforts to target IGF signaling for the treatment of breast cancer have been unsuccessful, due to a number of factors, most significantly the adverse effects of disrupting IGF signaling on normal glucose metabolism. We highlight here the recent discoveries that provide enthusiasm for continuing efforts to target IGF signaling for the treatment of breast cancer patients.

Abstract Background TREM2 is a transmembrane receptor that is predominantly expressed by microglia in the central nervous system. Rare variants in the TREM2 gene increase the risk for late-onset Alzheimer’s disease (AD). Soluble TREM2 (sTREM2) resulting from shedding of the TREM2 ectodomain can be detected in the cerebrospinal fluid (CSF) and is a surrogate measure of TREM2-mediated microglia function. CSF sTREM2 has been previously reported to increase at different clinical stages of AD, however, alterations in relation to Amyloid β-peptide (Aβ) deposition or additional pathological processes in the amyloid cascade (such as tau pathology or neurodegeneration) remain unclear. In the current cross-sectional study, we employed the biomarker-based classification framework recently proposed by the NIA-AA consensus guidelines, in combination with clinical staging, in order to examine the CSF sTREM2 alterations at early asymptomatic and symptomatic stages of AD. Methods A cross-sectional study of 1027 participants of the Alzheimer’s Disease Imaging Initiative (ADNI) cohort, including 43 subjects carrying TREM2 rare genetic variants, was conducted to measure CSF sTREM2 using a previously validated enzyme-linked immunosorbent assay (ELISA). ADNI participants were classified following the A/T/N framework, which we implemented based on the CSF levels of Aβ1-42 (A), phosphorylated tau (T) and total tau as a marker of neurodegeneration (N), at different clinical stages defined by the clinical dementia rating (CDR) score. Results CSF sTREM2 differed between TREM2 variants, whereas the p.R47H variant had higher CSF sTREM2, p.L211P had lower CSF sTREM2 than non-carriers. We found that CSF sTREM2 increased in early symptomatic stages of late-onset AD but, unexpectedly, we observed decreased CSF sTREM2 levels at the earliest asymptomatic phase when only abnormal Aβ pathology (A+) but no tau pathology or neurodegeneration (TN-), is present. Conclusions Aβ pathology (A) and tau pathology/neurodegeneration (TN) have differing associations with CSF sTREM2. While tau-related neurodegeneration is associated with an increase in CSF sTREM2, Aβ pathology in the absence of downstream tau-related neurodegeneration is associated with a decrease in CSF sTREM2.

Abstract The Worldwide Alzheimer's Disease Neuroimaging Initiative (WW‐ADNI) is a collaborative effort to investigate imaging and biofluid markers that can inform Alzheimer's disease treatment trials. It is a public‐private partnership that spans North America, Argentina, Australia, Canada, China, Japan, Korea, Mexico, and Taiwan. In 2004, ADNI researchers began a naturalistic, longitudinal study that continues today around the globe. Through several successive phases (ADNI‐1, ADNI‐GO, ADNI‐2, and ADNI‐3), the study has fueled amyloid and tau phenotyping and refined neuroimaging methodologies. WW‐ADNI researchers have successfully standardized analyses and openly share data without embargo, providing a rich data set for other investigators. On August 26, 2020, the Alzheimer's Association convened WW‐ADNI researchers who shared updates from ADNI‐3 and their vision for ADNI‐4.

Abstract Introduction Blood‐based assays to measure brain amyloid beta (Aβ) deposition are an attractive alternative to the cerebrospinal fluid (CSF)–based assays currently used in clinical settings. In this study, we examined different blood‐based assays to measure Aβ and how they compare among centers and assays. Methods Aliquots from 81 plasma samples were distributed to 10 participating centers. Seven immunological assays and four mass‐spectrometric methods were used to measure plasma Aβ concentrations. Results Correlations were weak for Aβ42 while Aβ40 correlations were stronger. The ratio Aβ42/Aβ40 did not improve the correlations and showed weak correlations. Discussion The poor correlations for Aβ42 in plasma might have several potential explanations, such as the high levels of plasma proteins (compared to CSF), sensitivity to pre‐analytical sample handling and specificity, and cross‐reactivity of different antibodies. Different methods might also measure different pools of plasma Aβ42. We, however, hypothesize that greater correlations might be seen in future studies because many of the methods have been refined during completion of this study.

Abstract Progranulin (PGRN) is predominantly expressed by microglia in the brain, and genetic and experimental evidence suggests a critical role in Alzheimer's disease (AD). We asked whether PGRN expression is changed in a disease severity‐specific manner in AD. We measured PGRN in cerebrospinal fluid (CSF) in two of the best‐characterized AD patient cohorts, namely the Dominant Inherited Alzheimer's Disease Network (DIAN) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). In carriers of AD causing dominant mutations, cross‐sectionally assessed CSF PGRN increased over the course of the disease and significantly differed from non‐carriers 10 years before the expected symptom onset. In late‐onset AD, higher CSF PGRN was associated with more advanced disease stages and cognitive impairment. Higher CSF PGRN was associated with higher CSF soluble TREM2 (triggering receptor expressed on myeloid cells 2) only when there was underlying pathology, but not in controls. In conclusion, we demonstrate that, although CSF PGRN is not a diagnostic biomarker for AD, it may together with sTREM2 reflect microglial activation during the disease.

Abstract Background The APOE ε4 allele is the most significant common genetic risk factor for late-onset Alzheimer’s disease (LOAD). The region surrounding APOE on chromosome 19 has also shown consistent association with LOAD. However, no common variants in the region remain significant after adjusting for APOE genotype. We report a rare variant association analysis of genes in the vicinity of APOE with cerebrospinal fluid (CSF) and neuroimaging biomarkers of LOAD. Methods Whole genome sequencing (WGS) was performed on 817 blood DNA samples from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Sequence data from 757 non-Hispanic Caucasian participants was used in the present analysis. We extracted all rare variants (MAF (minor allele frequency)

The insulin-like growth factor-1 (IGF-1) signaling pathway has been implicated in non-small cell lung cancer (NSCLC) outcomes and resistance to targeted therapies. However, little is known regarding the molecular mechanisms by which this pathway contributes to the biology of NSCLC. The insulin receptor substrate (IRS) proteins are cytoplasmic adaptor proteins that signal downstream of the IGF-1R and determine the functional outcomes of this signaling pathway. In this study, we assessed the expression patterns of IRS-1 and IRS-2 in NSCLC to identify associations between IRS-1 and IRS-2 expression levels and survival outcomes in the two major histological subtypes of NSCLC, adenocarcinoma (ADC) and squamous cell carcinoma (SCC). High IRS-2 expression was significantly associated with decreased overall survival in adenocarcinoma (ADC) patients, whereas low IRS-1 cytoplasmic expression showed a trend toward association with decreased overall survival in squamous cell carcinoma (SCC) patients. Tumors with low IRS-1 and high IRS-2 expression were found to be associated with poor outcomes in ADC and SCC, indicating a potential role for IRS-2 in the aggressive behavior of NSCLC. Our results suggest distinct contributions of IRS-1 and IRS-2 to the biology of ADC and SCC that impact disease progression.

Mitochondrial DNA regulates mitochondrial function which is altered in both idiopathic and familial forms of Parkinson's disease. To investigate whether these two disease forms exhibit an altered regulation of mitochondrial DNA we measured cell free mitochondrial DNA content in cerebrospinal fluid (CSF) from idiopathic and LRRK2-related Parkinson's disease patients. The concentration of mitochondrial DNA was measured using a digital droplet polymerase chain reaction technique in a total of 98 CSF samples from a cohort of subjects including: 20 LRRK2G2019S mutation carriers with Parkinson's disease, 26 asymptomatic LRRK2G2019S mutation carriers, 31 patients with idiopathic Parkinson's disease and 21 first-degree relatives of LRRK2 Parkinson's disease patients without the mutation. Here we report that LRRK2G2019S mutation carriers with Parkinson's disease exhibit a high concentration of mitochondrial DNA in CSF compared with asymptomatic LRRK2G2019S mutation carriers and with idiopathic Parkinson's disease patients. In addition, idiopathic, but not LRRK2 Parkinson's disease is associated with low CSF concentration of α-synuclein. These results show that high mitochondrial DNA content in CSF distinguishes idiopathic from LRRK2-related Parkinson's disease suggesting that different biochemical pathways underlie neurodegeneration in these two disorders.

Antecedentes : El interés en las necesidades de apoyo de las personas con discapacidad intelectual debe centrarse en la evaluación del patrón e intensidad de los apoyos reque - ridos para realizar las actividades diarias. Cuando se evalúan estas necesidades en niños, se debe considerar además la influencia de la edad. Método : Se evaluaron 450 personas con discapacidad intelectual (5-16 años) mediante la versión española de la SIS-C. La invariancia de medida y las diferencias latentes fueron analizadas relacionando la mues - tra española con la muestra normativa de la versión en inglés. Los modelos desarrollados para la creación de baremos se utilizaron para estudiar las equivalencias de medida en los distintos grupos de edad y las diferencias latentes de sus medias, varianzas y desvia - ciones típicas. Resultados : Los ítems de la versión española de la SIS-C son fiables para medir las necesidades de apoyo en personas de entre 5 y 16 años. A nivel latente, los datos mostraron diferencias en las medias de las puntuaciones de diferentes grupos de edad. Conclusiones : Pueden utilizarse los mismos ítems para medir las necesidades de apoyo de niños y adolescentes, pero debe considerarse la influencia de la edad tanto en la creación de baremos como en la planificación de apoyos.

Despite growing research efforts, no reliable biomarker currently exists for the diagnosis and prognosis of multiple system atrophy (MSA). Such biomarkers are urgently needed to improve diagnostic accuracy, prognostic guidance and also to serve as efficacy measures or surrogates of target engagement for future clinical trials. We here review candidate fluid biomarkers for MSA and provide considerations for further developments and harmonization of standard operating procedures. A PubMed search was performed until April 24, 2015 to review the literature with regard to candidate blood and cerebrospinal fluid (CSF) biomarkers for MSA. Abstracts of 1760 studies were retrieved and screened for eligibility. The final list included 60 studies assessing fluid biomarkers in patients with MSA. Most studies have focused on alpha-synuclein, markers of axonal degeneration or catecholamines. Their results suggest that combining several CSF fluid biomarkers may be more successful than using single markers, at least for the diagnosis. Currently, the clinically most useful markers may comprise a combination of the light chain of neurofilament (which is consistently elevated in MSA compared to controls and Parkinson’s disease), metabolites of the catecholamine pathway and proteins such as α-synuclein, DJ-1 and total-tau. Beyond future efforts in biomarker discovery, the harmonization of standard operating procedures will be crucial for future success.

Abstract The characterization of cells with tumour initiating potential is significant for advancing our understanding of cancer and improving therapy. Aggressive, triple‐negative breast cancers (TNBCs) are enriched for tumour‐initiating cells (TICs). We investigated that hypothesis that VEGF receptors expressed on TNBC cells mediate autocrine signalling that contributes to tumour initiation. We discovered the VEGF receptor neuropilin‐2 (NRP2) is expressed preferentially on TICs, involved in the genesis of TNBCs and necessary for tumour initiation. The mechanism by which NRP2 signalling promotes tumour initiation involves stimulation of the α6β1 integrin, focal adhesion kinase‐mediated activation of Ras/MEK signalling and consequent expression of the Hedgehog effector GLI1. GLI1 also induces BMI‐1, a key stem cell factor, and it enhances NRP2 expression and the function of α6β1, establishing an autocrine loop. NRP2 can be targeted in vivo to retard tumour initiation. These findings reveal a novel autocrine pathway involving VEGF/NRP2, α6β1 and GLI1 that contributes to the initiation of TNBC. They also support the feasibility of NRP2‐based therapy for the treatment of TNBC that targets and impedes the function of TICs. → See accompanying article http://dx.doi.org/10.1002/emmm.201302505

Therapies targeting the type I insulin-like growth factor receptor (IGF-1R) have not been developed with predictive biomarkers to identify tumors with receptor activation. We have previously shown that the insulin receptor substrate (IRS) adaptor proteins are necessary for linking IGF1R to downstream signaling pathways and the malignant phenotype in breast cancer cells. The purpose of this study was to identify gene expression profiles downstream of IGF1R and its two adaptor proteins. IRS-null breast cancer cells (T47D-YA) were engineered to express IRS-1 or IRS-2 alone and their ability to mediate IGF ligand-induced proliferation, motility, and gene expression determined. Global gene expression signatures reflecting IRS adaptor specific and primary vs. secondary ligand response were derived (Early IRS-1, Late IRS-1, Early IRS-2 and Late IRS-2) and functional pathway analysis examined. IRS isoforms mediated distinct gene expression profiles, functional pathways, and breast cancer subtype association. For example, IRS-1/2-induced TGFb2 expression and blockade of TGFb2 abrogated IGF-induced cell migration. In addition, the prognostic value of IRS proteins was significant in the luminal B breast tumor subtype. Univariate and multivariate analyses confirmed that IRS adaptor signatures correlated with poor outcome as measured by recurrence-free and overall survival. Thus, IRS adaptor protein expression is required for IGF ligand responses in breast cancer cells. IRS-specific gene signatures represent accurate surrogates of IGF activity and could predict response to anti-IGF therapy in breast cancer.

Objective: Our goal was to evaluate the association APOE with amyloid deposition, cerebrospinal fluid levels (CSF) of Aβ, tau, and p-tau, brain atrophy, cognition and cognitive complaints in E-MCI patients and cognitively healthy older adults (HC) in the ADNI-2 cohort. Methods: 209 E-MCI and 123 HC participants from the ADNI-2 cohort were included. We evaluated the impact of diagnostic status (E-MCI vs. HC) and APOE ε4 status (ε4 positive vs. ε4 negative) on cortical amyloid deposition (AV-45/Florbetapir SUVR PET scans), brain atrophy (structural MRI scans processed using voxel-based morphometry and Freesurfer version 5.1), CSF levels of Aβ, tau, and p-tau, and cognitive performance and complaints. Results: E-MCI participants showed significantly impaired cognition, higher levels of cognitive complaints, greater levels of tau and p-tau, and subcortical and cortical atrophy relative to HC participants (p

Different inflammatory and metabolic pathways have been associated with Alzheimeŕs disease (AD). However, only recently multi-analyte panels to study a large number of molecules in well characterized cohorts have been made available. These panels could help identify molecules that point to the affected pathways. We studied the relationship between a panel of plasma biomarkers (Human DiscoveryMAP) and presence of AD-like brain atrophy patterns defined by a previously published index (SPARE-AD) at baseline in subjects of the ADNI cohort. 818 subjects had MRI-derived SPARE-AD scores, of these subjects 69% had plasma biomarkers and 51% had CSF tau and Aβ measurements. Significant analyte-SPARE-AD and analytes correlations were studied in adjusted models. Plasma cortisol and chromogranin A showed a significant association that did not remain significant in the CSF signature adjusted model. Plasma macrophage inhibitory protein-1α and insulin-like growth factor binding protein 2 showed a significant association with brain atrophy in the adjusted model. Cortisol levels showed an inverse association with tests measuring processing speed. Our results indicate that stress and insulin responses and cytokines associated with recruitment of inflammatory cells in MCI-AD are associated with its characteristic AD-like brain atrophy pattern and correlate with clinical changes or CSF biomarkers.

A central means by which mammalian cells respond to low oxygen tension is through the activation of the transcription factor HIF-1 (hypoxia-inducible factor-1). Under normoxic conditions, HIF-1α (the α subunit of HIF-1) is targeted for rapid degradation by the ubiquitin–proteasome pathway. Under hypoxic conditions, this degradation is inhibited, thereby leading to the stabilization and activation of HIF-1α. Here, we report the identification of IOP1 (iron-only hydrogenase-like protein 1), a protein homologous with enzymes present in anaerobic organisms that contain a distinctive iron–sulfur cluster. IOP1 is present in a broad range of cell types. Knockdown of IOP1 using siRNA (small interfering RNA) in mammalian cells increases protein levels of HIF-1α under both normoxic and hypoxic conditions, and augments hypoxia-induced HRE (hypoxia response element) reporter gene and endogenous HIF-1α target gene expressions. We find that IOP1 knockdown up-regulates HIF-1α mRNA levels, thereby providing a mechanism by which knockdown induces the observed effects. The results collectively provide evidence that IOP1 is a component of the protein network that regulates HIF-1α in mammalian cells. [ABSTRACT FROM AUTHOR]

Abstract Background Alzheimer’s disease (AD)-related tauopathy can be measured with CSF phosphorylated tau (pTau) and tau PET. We aim to investigate the associations between these measurements and their relative ability to predict subsequent disease progression. Methods In 219 cognitively unimpaired and 122 impaired Alzheimer’s Disease Neuroimaging Initiative participants with concurrent amyloid-β (Aβ) PET (18F-florbetapir or 18F-florbetaben), 18F-flortaucipir (FTP) PET, CSF measurements, structural MRI, and cognition, we examined inter-relationships between these biomarkers and their predictions of subsequent FTP and cognition changes. Results The use of a CSF pTau/Aβ40 ratio eliminated positive associations we observed between CSF pTau alone and CSF Aβ42 in the normal Aβ range likely reflecting individual differences in CSF production rather than pathology. Use of the CSF pTau/Aβ40 ratio also increased expected associations with Aβ PET, FTP PET, hippocampal volume, and cognitive decline compared to pTau alone. In Aβ+ individuals, abnormal CSF pTau/Aβ40 only individuals (26.7%) were 4 times more prevalent (p

Abstract Pathological tau aggregates in Alzheimer’s disease (AD) and frontotemporal lobar degeneration-tau (FTLD-tau) adopt distinct conformations differentiated by the AD-tau specific monoclonal antibody (mAb) GT-38 that are not readily visualized using phosphorylation-specific anti-tau mAbs. To determine the extent of co-morbid AD-tau pathology in FTLD-tau, we performed immunohistochemical (IHC) staining with GT-38 and assigned Braak stages of AD-tau in a cohort 180 FTLD-tau cases consisting of corticobasal degeneration (CBD; n = 49), progressive supranuclear palsy (PSP; n = 109), and Pick’s disease (PiD; n = 22). Nearly two-thirds of patients (n = 115 of 180, 63.8%) with FTLD-tau had some degree of comorbid AD-tau pathology and 20.5% of the FTLD-tau cohort had Braak stage ≥B2, consistent with medium-to-high-level AD neuropathological change (ADNPC). The PSP group had the highest frequency of medium-high AD-tau pathology compared to other tauopathies (PSP = 31/109, 28.4%; Picks = 2/22, 9.1%, CBD = 4/49, 8.2%) but neuropathological diagnosis was not found to be a significant independent predictor of medium-high AD Braak stage in a multivariate model after accounting for age at death (OR = 1.09; 95% CI = 1.03–1.15; p = 0.002) and CERAD plaque scores (OR = 3.75, 95% CI = 1.58–8.89; p = 0.003), suggesting there is no predilection for a specific FTLD tauopathy to develop AD-tau co-pathology after accounting for age. Patients with FTLD-tau who had, clinically significant, medium-high AD-tau pathology had significantly higher antemortem CSF levels of both total-tau (t-tau; mean = 89.98 pg/ml, SD = 36.70 pg/ml) and phosphorylated-tau (p-tau; mean = 20.45 pg/ml, SD = 9.31 pg/ml) compared to patients with negligible-low AD-tau, t-tau (mean = 43.04 pg/ml, SD = 25.40 pg/ml) and p-tau (mean = 11.90 pg/ml, SD = 4.48 pg/ml) (p ≤ 0.001 both). Finally, in an exploratory analysis in our largest pathology group (PSP) we find an association of GT-38 AD-tau Braak stage with lower baseline MMSE (p = 0.03). Together, these finding validate the use of GT-38 to selectively detect AD-tau pathology in the context of FTLD-tau and provides a novel tool to investigate associations of clinical phenotypes amongst co-morbid tauopathies.

Abstract Background Alzheimer’s disease (AD) is a complex neurodegenerative disorder characterized by neuropathologic changes involving beta-amyloid (Aβ), tau, neuronal loss, and other associated biological events. While levels of cerebrospinal fluid (CSF) Aβ and tau peptides have enhanced the antemortem detection of AD-specific changes, these two markers poorly reflect the severity of cognitive and functional deficits in people with altered Aβ and tau levels. While multiple previous studies identified non-Aβ, non-tau proteins as candidate neurodegenerative markers to inform the A/T/N biomarker scheme of AD, few have advanced beyond association with clinical AD diagnosis. Here we analyzed nine promising neurodegenerative markers in a three-centered cohort using independent assays to identify candidates most likely to complement Aβ and tau in the A/T/N framework. Methods CSF samples from 125 subjects recruited at the three centers were exchanged such that each of the nine previously identified biomarkers can be measured at one of the three centers. Subjects were classified according to cognitive status and CSF AD biomarker profiles as having normal cognition and normal CSF (n = 31), normal cognition and CSF consistent with AD (n = 13), mild cognitive impairment and normal CSF (n = 13), mild cognitive impairment with CSF consistent with AD (n = 23), AD dementia (n = 32; CSF consistent with AD), and other non-AD dementia (n = 13; CSF not consistent with AD). Results Three biomarkers were identified to differ among the AD stages, including neurofilament light chain (NfL; p

Abstract Introduction An Elecsys® Amyloid β (Aβ [1–42]) immunoassay cutoff for classification of patients with Alzheimer's disease was investigated. Methods Cerebrospinal fluid samples collected from patients with mild‐to‐moderate Alzheimer's disease were analyzed by Elecsys® immunoassays: (1) Aβ (1–42), (2) total tau, and (3) phosphorylated tau. Cutoffs (Aβ [1–42] and ratios with tau) were estimated by method comparison between AlzBio3 (n = 206), mixture modeling (n = 216), and concordance with florbetapir F 18 imaging‐based classification (n = 75). Results A 1065‐pg/mL (95% confidence interval: 985–1153) Elecsys® Aβ (1–42) cutoff provided 94% overall percentage agreement with AlzBio3. Comparable cutoff estimates (95% confidence interval) were derived from mixture modeling (equally weighted: 1017 [949–1205] pg/mL; prevalence weighted: 1172 [1081–1344] pg/mL) and concordance with florbetapir F 18 imaging (visual read: 1198 [998–1591] pg/mL; automated: 1198 [1051–1638] pg/mL). Discussion Based on three approaches, a 1100‐pg/mL Elecsys® Aβ (1–42) cutoff is suitable for clinical trials with similar populations and preanalytical handling.

We developed a merged younger-older adult template of the fornix and demonstrated its utility for studies of aging and preclinical Alzheimer's disease (AD). In Experiment 1, probabilistic tractography was used to reconstruct the fornix in younger and older adults and successful streamlines were then averaged to create a merged template in standard space. The new template includes the majority of the fornix from the hippocampal formation to the subcallosal region and the thalamus/hypothalamus. In Experiment 2, the merged template was validated as an appropriate measure for studies of aging, with comparisons against manual tracing measures indicating identical spatial coverage in younger and older adult groups. In Experiment 3, the merged template was found to outperform age-specific templates in measures of sensitivity and specificity computed on diffusion tensor imaging data of an independent participant cohort. In Experiment 4, relevance to preclinical AD was demonstrated via associations between fractional anisotropy within the new fornix template and cerebrospinal fluid markers of AD pathology (Aβ42 and the t-tau/Aβ42 ratio) in a third independent cohort of cognitively normal older adults. Our new template provides an appropriate measure for use in future studies seeking to characterize microstructural alterations in the fornix associated with aging and preclinical AD.

Alzheimer's disease (AD), including its mild cognitive impairment (MCI) phase that may or may not progress into the AD, is the most ordinary form of dementia. It is extremely important to correctly identify patients during the MCI stage because this is the phase where AD may or may not develop. Thus, it is crucial to predict outcomes during this phase. Thus far, many researchers have worked on only using a single modality of a biomarker for the diagnosis of AD or MCI. Although recent studies show that a combination of one or more different biomarkers may provide complementary information for the diagnosis, it also increases the classification accuracy distinguishing between different groups. In this paper, we propose a novel machine learning-based framework to discriminate subjects with AD or MCI utilizing a combination of four different biomarkers: fluorodeoxyglucose positron emission tomography (FDG-PET), structural magnetic resonance imaging (sMRI), cerebrospinal fluid (CSF) protein levels, and Apolipoprotein-E (APOE) genotype. The Alzheimer's Disease Neuroimaging Initiative (ADNI) baseline dataset was used in this study. In total, there were 158 subjects for whom all four modalities of biomarker were available. Of the 158 subjects, 38 subjects were in the AD group, 82 subjects were in MCI groups (including 46 in MCIc [MCI converted; conversion to AD within 24 months of time period], and 36 in MCIs [MCI stable; no conversion to AD within 24 months of time period]), and the remaining 38 subjects were in the healthy control (HC) group. For each image, we extracted 246 regions of interest (as features) using the Brainnetome template image and NiftyReg toolbox, and later we combined these features with three CSF and two APOE genotype features obtained from the ADNI website for each subject using early fusion technique. Here, a different kernel-based multiclass support vector machine (SVM) classifier with a grid-search method was applied. Before passing the obtained features to the classifier, we have used truncated singular value decomposition (Truncated SVD) dimensionality reduction technique to reduce high dimensional features into a lower-dimensional feature. As a result, our combined method achieved an area under the receiver operating characteristic (AU-ROC) curve of 98.33, 93.59, 96.83, 94.64, 96.43, and 95.24% for AD vs. HC, MCIs vs. MCIc, AD vs. MCIs, AD vs. MCIc, HC vs. MCIc, and HC vs. MCIs subjects which are high relative to single modality results and other state-of-the-art approaches. Moreover, combined multimodal methods have improved the classification performance over the unimodal classification.

Mild cognitive impairment (MCI) is a transitional state between the cognitive changes in normal aging and Alzheimer’s disease (AD), which induces abnormalities in specific brain regions. Previous studies showed that paired helical filaments Tau (PHF-Tau) protein is a potential pathogenic protein which may cause abnormal brain function and structure in MCI and AD patients. However, the understanding of the PHF-Tau protein network in MCI patients is limited. In this study, 225 subjects with PHF-Tau Positron Emission Tomography (PET) images were divided into four groups based on whether they carried Apolipoprotein E ε4 (APOE 4) or abnormal cerebrospinal fluid Total-Tau (CSF T-Tau). They are two important pathogenic factors that might cause cognitive function impairment. The four groups were: individuals harboring CSF T-Tau pathology but no APOE 4 (APOE 4−T+); APOE 4 carriers with normal CSF T-Tau (APOE 4+T−); APOE 4 carriers with abnormal CSF T-Tau (APOE 4+T+); and APOE 4 noncarriers with abnormal CSF T-Tau (APOE 4−T−). We explored the topological organization of PHF-Tau networks in these four groups and calculated five kinds of network properties: clustering coefficient, shortest path length, Q value of modularity, nodal centrality and degree. Our findings showed that compared with APOE 4−T− group, the other three groups showed different alterations in the clustering coefficient, shortest path length, Q value of modularity, nodal centrality and degree. Simultaneously, voxel-level analysis was conducted and the results showed that compared with APOE 4−T− group, the other three groups were found increased PHF-Tau distribution in some brain regions. For APOE 4+T+ group, positive correlation was found between the value of PHF-Tau distribution in altered regions and Functional Assessment Questionnaire (FAQ) score. Our results indicated that the effects of APOE 4 and abnormal CSF T-Tau may induce abnormalities of PHF-Tau protein and APOE 4 has a greater impact on PHF-Tau than abnormal CSF T-Tau. Our results may be particularly helpful in uncovering the pathophysiology underlying the cognitive dysfunction in MCI patients.

BackgroundNon-invasive brain stimulation (NIBS) has been widely used to treat mild cognitive impairment (MCI). However, there exists no consensus on the best stimulation sites.ObjectiveTo explore potential stimulation locations for NIBS treatment in patients with MCI, combining meta- and resting state functional connectivity (rsFC) analyses.MethodsThe meta-analysis was conducted to identify brain regions associated with MCI. Regions of interest (ROIs) were extracted based on this meta-analysis. The rsFC analysis was applied to 45 MCI patients to determine brain surface regions that are functionally connected with the above ROIs.ResultsWe found that the dorsolateral prefrontal cortex (DLPFC) and inferior frontal gyrus (IFG) were the overlapping brain regions between our results and those of previous studies. In addition, we recommend that the temporoparietal junction (including the angular gyrus), which was found in both the meta- and rsFC analysis, should be considered in NIBS treatment of MCI. Furthermore, the bilateral orbital prefrontal gyrus, inferior temporal gyrus, medial superior frontal gyrus, and right inferior occipital gyrus may be potential brain stimulation sites for NIBS treatment of MCI.ConclusionOur results provide several potential sites for NIBS, such as the DLFPC and IFG, and may shed light on the locations of NIBS sites in the treatment of patients with MCI.

Collecting multiple modalities of neuroimaging data on the same subject is increasingly becoming the norm in clinical practice and research. Fusing multiple modalities to find related patterns is a challenge in neuroimaging analysis. Canonical correlation analysis (CCA) is commonly used as a symmetric data fusion technique to find related patterns among multiple modalities. In CCA-based data fusion, principal component analysis (PCA) is frequently applied as a preprocessing step to reduce data dimension followed by CCA on dimension-reduced data. PCA, however, does not differentiate between informative voxels from non-informative voxels in the dimension reduction step. Sparse PCA (sPCA) extends traditional PCA by adding sparse regularization that assigns zero weights to non-informative voxels. In this study, sPCA is incorporated into CCA-based fusion analysis and applied on neuroimaging data. A cross-validation method is developed and validated to optimize the parameters in sPCA. Different simulations are carried out to evaluate the improvement by introducing sparsity constraint to PCA. Four fusion methods including sPCA+CCA, PCA+CCA, parallel ICA and sparse CCA were applied on structural and functional magnetic resonance imaging data of mild cognitive impairment subjects and normal controls. Our results indicate that sPCA significantly can reduce the impact of non-informative voxels and lead to improved statistical power in uncovering disease-related patterns by a fusion analysis.

Recent developments of tau Positron Emission Tomography (PET) allows assessment of regional neurofibrillary tangles (NFTs) deposition in human brain. Among the tau PET molecular probes, 18F-AV1451 is characterized by high selectivity for pathologic tau aggregates over amyloid plaques, limited non-specific binding in white and gray matter, and confined off-target binding. The objectives of the study are (1) to quantitatively characterize regional brain tau deposition measured by 18F-AV1451 PET in cognitively normal older adults (CN), mild cognitive impairment (MCI), and AD participants; (2) to evaluate the correlations between cerebrospinal fluid (CSF) biomarkers or Mini-Mental State Examination (MMSE) and 18F-AV1451 PET standardized uptake value ratio (SUVR); and (3) to evaluate the partial volume effects on 18F-AV1451 brain uptake.Methods: The study included total 115 participants (CN = 49, MCI = 58, and AD = 8) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Preprocessed 18F-AV1451 PET images, structural MRIs, and demographic and clinical assessments were downloaded from the ADNI database. A reblurred Van Cittertiteration method was used for voxelwise partial volume correction (PVC) on PET images. Structural MRIs were used for PET spatial normalization and region of interest (ROI) definition in standard space. The parametric images of 18F-AV1451 SUVR relative to cerebellum were calculated. The ROI SUVR measurements from PVC and non-PVC SUVR images were compared. The correlation between ROI 18F-AV1451 SUVR and the measurements of MMSE, CSF total tau (t-tau), and phosphorylated tau (p-tau) were also assessed.Results:18F-AV1451 prominently specific binding was found in the amygdala, entorhinal cortex, parahippocampus, fusiform, posterior cingulate, temporal, parietal, and frontal brain regions. Most regional SUVRs showed significantly higher uptake of 18F-AV1451 in AD than MCI and CN participants. SUVRs of small regions like amygdala, entorhinal cortex and parahippocampus were statistically improved by PVC in all groups (p < 0.01). Although there was an increasing tendency of 18F-AV-1451 SUVRs in MCI group compared with CN group, no significant difference of 18F-AV1451 deposition was found between CN and MCI brains with or without PVC (p > 0.05). Declined MMSE score was observed with increasing 18F-AV1451 binding in amygdala, entorhinal cortex, parahippocampus, and fusiform. CSF p-tau was positively correlated with 18F-AV1451 deposition. PVC improved the results of 18F-AV-1451 tau deposition and correlation studies in small brain regions.Conclusion: The typical deposition of 18F-AV1451 tau PET imaging in AD brain was found in amygdala, entorhinal cortex, fusiform and parahippocampus, and these regions were strongly associated with cognitive impairment and CSF biomarkers. Although more deposition was observed in MCI group, the 18F-AV-1451 PET imaging could not differentiate the MCI patients from CN population. More tau deposition related to decreased MMSE score and increased level of CSF p-tau, especially in ROIs of amygdala, entorhinal cortex and parahippocampus. PVC did improve the results of tau deposition and correlation studies in small brain regions and suggest to be routinely used in 18F-AV1451 tau PET quantification.

Objective: To test the validity of a common measure of health-related quality of life (Short-Form-36 [SF-36]) in cognitively healthy older adults living in rural and urban Costa Rica. Method: Confirmatory factor analysis was applied to SF-36 data collected in 250 older adults from San Jose and Guanacaste, Costa Rica. Results: The best fitting model for the SF-36 was an eight first-order factor structure. A high correlation between the Mental Component Summary and Physical Component Summary scores was found. Region differences indicated that rural dwellers perceive a poorer health-related quality of life compared with the urban group. Discussion: Costa Rican older adults perceived health as a unidimensional construct. Age and urbanity of older adult Costa Ricans should be appreciated when trying to measure self-reported physical and mental health. Cultural context of the individuals should be considered when studying health-related quality of life.

Alzheimer's disease (AD) is a complex neurodegenerative disease driven by multiple interacting pathophysiological processes that ultimately results in synaptic loss, neuronal death, and dementia. We implemented a fit-for-purpose modeled approach to qualify a broad selection of commercially available immunoassays and evaluate the biotemporal stability of analytes across five pathophysiological domains of interest in AD, including core amyloid-β (Aβ) and tau AD biomarkers, neurodegeneration, inflammation/immune modulation, neurovascular injury, and metabolism/oxidative stress.Paired baseline and eight-week CSFs from twenty participants in a clinical drug trial for mild cognitive impairment (MCI) or mild dementia due to AD were used to evaluate sensitivity, intra-assay precision, inter-assay replicability, and eight-week biotemporal stability for sixty unique analytes measured with commercially available single- and multi-plex ELISA assays. Coefficients of variation (CV) were calculated, and intraclass correlation and Wilcoxon signed rank tests were applied.We identified 32 biomarker candidates with good to excellent performance characteristics according to assay technical performance and CSF analyte biotemporal stability cut-off criteria. These included: 1) the core AD biomarkers Aβ1-42, Aβ1-40, Aβ1-38, and total tau; 2) non-Aβ, non-tau neurodegeneration markers NfL and FABP3; 3) inflammation/immune modulation markers IL-6, IL-7, IL-8, IL-12/23p40, IL-15, IL-16, MCP-1, MDC, MIP-1β, and YKL-40; 4) neurovascular markers Flt-1, ICAM-1, MMP-1, MMP-2, MMP-3, MMP-10, PlGF, VCAM-1, VEGF, VEGF-C, and VEGF-D; and 5) metabolism/oxidative stress markers 24-OHC, adiponectin, leptin, soluble insulin receptor, and 8-OHdG.Assays for these CSF analytes demonstrate consistent sensitivity, reliability, and biotemporally stability for use in a multiple pathophysiological CSF biomarker panel to profile AD. Their qualification enables further investigation for use in AD diagnosis, staging and progression, disease mechanism profiling, and clinical trials.

Abstract Introduction The dynamic range of cerebrospinal fluid (CSF) amyloid β (Aβ1–42) measurement does not parallel to cognitive changes in Alzheimer's disease (AD) and cognitively normal (CN) subjects across different studies. Therefore, identifying novel proteins to characterize symptomatic AD samples is important. Methods Proteins were profiled using a multianalyte platform by Rules Based Medicine (MAP‐RBM). Due to underlying heterogeneity and unbalanced sample size, we combined subjects (344 AD and 325 CN) from three cohorts: Alzheimer's Disease Neuroimaging Initiative, Penn Center for Neurodegenerative Disease Research of the University of Pennsylvania, and Knight Alzheimer's Disease Research Center at Washington University in St. Louis. We focused on samples whose cognitive and amyloid status was consistent. We performed linear regression (accounted for age, gender, number of apolipoprotein E (APOE) e4 alleles, and cohort variable) to identify amyloid‐related proteins for symptomatic AD subjects in this largest ever CSF–based MAP‐RBM study. ANOVA and Tukey's test were used to evaluate if these proteins were related to cognitive impairment changes as measured by mini‐mental state examination (MMSE). Results Seven proteins were significantly associated with Aβ1–42 levels in the combined cohort (false discovery rate adjusted P < .05), of which lipoprotein a (Lp(a)), prolactin (PRL), resistin, and vascular endothelial growth factor (VEGF) have consistent direction of associations across every individual cohort. VEGF was strongly associated with MMSE scores, followed by pancreatic polypeptide and immunoglobulin A (IgA), suggesting they may be related to staging of AD. Discussion Lp(a), PRL, IgA, and tissue factor/thromboplastin have never been reported for AD diagnosis in previous individual CSF–based MAP‐RBM studies. Although some of our reported analytes are related to AD pathophysiology, other's roles in symptomatic AD samples worth further explorations.

Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI), the converted MCI (cMCI), and the normal control (NC) groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI) were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM). An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI–cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI–NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI–NC comparison. The best performances obtained by the SVM classifier using the essential features were 5–40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and predict the risk of its conversion to Alzheimer's disease.