%0 Journal Article %J J Alzheimers Dis %D 2018 %T Association of Cerebrospinal Fluid (CSF) Insulin with Cognitive Performance and CSF Biomarkers of Alzheimer's Disease. %A Geijselaers, Stefan L C %A Aalten, Pauline %A Ramakers, Inez H G B %A De Deyn, Peter Paul %A Heijboer, Annemieke C %A Koek, Huiberdina L %A OldeRikkert, Marcel G M %A Papma, Janne M %A Reesink, Fransje E %A Smits, Lieke L %A Stehouwer, Coen D A %A Teunissen, Charlotte E %A Verhey, Frans R J %A van der Flier, Wiesje M %A Biessels, Geert Jan %K Aged %K Alzheimer Disease %K Amyloid beta-Peptides %K Apolipoprotein E4 %K Brain %K Cognition Disorders %K Female %K Humans %K Insulin %K Male %K Mental Status Schedule %K Middle Aged %K Neuropsychological Tests %K Peptide Fragments %K Signal Transduction %K tau Proteins %X

BACKGROUND: Abnormal insulin signaling in the brain has been linked to Alzheimer's disease (AD).

OBJECTIVE: To evaluate whether cerebrospinal fluid (CSF) insulin levels are associated with cognitive performance and CSF amyloid-β and Tau. Additionally, we explore whether any such association differs by sex or APOE ɛ4 genotype.

METHODS: From 258 individuals participating in the Parelsnoer Institute Neurodegenerative Diseases, a nationwide multicenter memory clinic population, we selected 138 individuals (mean age 66±9 years, 65.2% male) diagnosed with subjective cognitive impairment (n = 45), amnestic mild cognitive impairment (n = 44), or AD (n = 49), who completed a neuropsychological assessment, including tests of global cognition and memory performance, and who underwent lumbar puncture. We measured CSF levels of insulin, amyloid-β1-42, total (t-)Tau, and phosphorylated (p-)Tau.

RESULTS: CSF insulin levels did not differ between the diagnostic groups (p = 0.136). Across the whole study population, CSF insulin was unrelated to cognitive performance and CSF biomarkers of AD, after adjustment for age, sex, body mass index, diabetes status, and clinic site (all p≥0.131). Importantly, however, we observed effect modification by sex and APOE ɛ4 genotype. Specifically, among women, higher insulin levels in the CSF were associated with worse global cognition (standardized regression coefficient -0.483; p = 0.008) and higher p-Tau levels (0.353; p = 0.040). Among non-carriers of the APOE ɛ4 allele, higher CSF insulin was associated with higher t-Tau (0.287; p = 0.008) and p-Tau (0.246; p = 0.029).

CONCLUSION: Our findings provide further evidence for a relationship between brain insulin signaling and AD pathology. It also highlights the need to consider sex and APOE ɛ4 genotype when assessing the role of insulin.

%B J Alzheimers Dis %V 61 %P 309-320 %8 2018 %G eng %N 1 %1 http://www.ncbi.nlm.nih.gov/pubmed/29154275?dopt=Abstract %R 10.3233/JAD-170522 %0 Journal Article %J J Alzheimers Dis %D 2016 %T Heterogeneous Language Profiles in Patients with Primary Progressive Aphasia due to Alzheimer's Disease. %A Louwersheimer, Eva %A Keulen, M Antoinette %A Steenwijk, Martijn D %A Wattjes, Mike P %A Jiskoot, Lize C %A Vrenken, Hugo %A Teunissen, Charlotte E %A van Berckel, Bart N M %A van der Flier, Wiesje M %A Scheltens, Philip %A van Swieten, John C %A Pijnenburg, Yolande A L %K Aged %K Alzheimer Disease %K Aphasia, Primary Progressive %K Atrophy %K Biomarkers %K Brain %K Female %K Humans %K Language %K Language Tests %K Magnetic Resonance Imaging %K Male %K Mental Status Schedule %K Organ Size %K Positron-Emission Tomography %K Retrospective Studies %X

BACKGROUND: The logopenic variant of Primary Progressive Aphasia (lvPPA) is associated with underlying Alzheimer's disease (AD) pathology and characterized by impaired single word retrieval and repetition of phrases and sentences.

OBJECTIVE: We set out to study whether logopenic aphasia is indeed the prototypic language profile in PPA patients with biomarker evidence of underlying AD pathology and to correlate language profiles with cortical atrophy patterns on MRI.

METHODS: Inclusion criteria: (I) clinical diagnosis of PPA; (II) CSF profile and/or PiB-PET scan indicative for amyloid pathology; (III) availability of expert language evaluation. Based on language evaluation, patients were classified as lvPPA (fulfilling lvPPA core criteria), lvPPA extended (fulfilling core criteria plus other language disturbances), or PPA unclassifiable (not fulfilling lvPPA core criteria). Cortical atrophy patterns on MRI were visually rated and quantitative measurements of cortical thickness were performed using FreeSurfer.

RESULTS: We included 22 patients (age 67±7 years, 50% female, MMSE 21±6). 41% were classified as lvPPA, 36% as lvPPA extended with additional deficits in language comprehension and/or confrontation naming, and 23% as PPA unclassifiable. By both qualitative and quantitative measurements, patients with lvPPA showed mild global cortical atrophy on MRI, whereas patients with lvPPA extended showed more focal cortical atrophy, predominantly at the left tempo-parietal side. For PPA unclassifiable, qualitative measurements revealed a heterogeneous atrophy pattern.

CONCLUSION: Although most patients fulfilled the lvPPA criteria, we found that their language profiles were heterogeneous. The clinical and radiological spectrum of PPA due to underlying AD pathology is broader than pure lvPPA.

%B J Alzheimers Dis %V 51 %P 581-90 %8 2016 %G eng %N 2 %1 http://www.ncbi.nlm.nih.gov/pubmed/26890751?dopt=Abstract %R 10.3233/JAD-150812 %0 Journal Article %J J Alzheimers Dis %D 2016 %T Integrating Biomarkers for Underlying Alzheimer's Disease in Mild Cognitive Impairment in Daily Practice: Comparison of a Clinical Decision Support System with Individual Biomarkers. %A Rhodius-Meester, Hanneke F M %A Koikkalainen, Juha %A Mattila, Jussi %A Teunissen, Charlotte E %A Barkhof, Frederik %A Lemstra, Afina W %A Scheltens, Philip %A Lötjönen, Jyrki %A van der Flier, Wiesje M %K Aged %K Aged, 80 and over %K Algorithms %K Alzheimer Disease %K Area Under Curve %K Biomarkers %K Cognitive Dysfunction %K Cohort Studies %K Decision Support Systems, Clinical %K Disease Progression %K Female %K Humans %K Image Processing, Computer-Assisted %K Magnetic Resonance Imaging %K Male %K Mental Status Schedule %K Middle Aged %K Neuropsychological Tests %K Outcome Assessment (Health Care) %K Predictive Value of Tests %X

BACKGROUND: Recent criteria allow biomarkers to provide evidence of Alzheimer's disease (AD) pathophysiology. How they should be implemented in daily practice remains unclear, especially in mild cognitive impairment (MCI) patients.

OBJECTIVE: We evaluated how a clinical decision support system such as the PredictAD tool can aid clinicians to integrate biomarker evidence to support AD diagnosis.

METHODS: With available data on demographics, cerebrospinal fluid (CSF), and MRI, we trained the PredictAD tool on a reference population of 246 controls and 491 AD patients. We then applied the identified algorithm to 211 MCI patients. For comparison, we also classified patients based on individual biomarkers (MRI; CSF) and the NIA-AA criteria. Progression to dementia was used as outcome measure.

RESULTS: After a median follow up of 3 years, 72 (34%) MCI patients remained stable and 139 (66%) progressed to AD. The PredictAD tool assigned a likelihood of underlying AD to each patient (AUC 0.82). Excluding patients with missing data resulted in an AUC of 0.87. According to the NIA-AA criteria, half of the MCI patients had uninformative biomarkers, precluding an assignment of AD likelihood. A minority (41%) was assigned to high or low AD likelihood with good predictive value. The individual biomarkers showed best value for CSF total tau (AUC 0.86).

CONCLUSION: The ability of the PredictAD tool to identify AD pathophysiology was comparable to individual biomarkers. The PredictAD tool has the advantage that it assigns likelihood to all patients, regardless of missing or conflicting data, allowing clinicians to integrate biomarker data in daily practice.

%B J Alzheimers Dis %V 50 %P 261-70 %8 2016 %G eng %N 1 %1 http://www.ncbi.nlm.nih.gov/pubmed/26577521?dopt=Abstract %R 10.3233/JAD-150548