Introduction. While cerebrospinal fluid (CSF) core biomarkers have been considered diagnostic biomarkers for a long time, special attention has been recently dedicated to lipoproteins and metabolites that could be potentially associated with Alzheimer’s disease (AD) neurodegeneration. Herein, we aimed to investigate the relationship between the levels of CSF core biomarkers including Aβ-42, TAU, and P-TAU and plasma lipoproteins and metabolites of patients with AD from the baseline cohort of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. Method. Using the ADNI database, fourteen subclasses of lipoproteins as well as a number of lipids and fatty acids and low-molecular metabolites including amino acids, ketone bodies, and glycolysis-related metabolites in blood samples were measured as potential noninvasive markers, and their association with the CSF core biomarkers was statistically investigated controlling for age and gender. Results. A total number of 251 AD subjects were included, among whom 71 subjects were negative for the Apo-E ε4 allele and 150 were positive. There was no significant difference between the two groups regarding cognitive assessments, CSF core biomarkers, and lipoproteins and metabolites except the level of Aβ-42 (<svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="18.973pt" style="vertical-align:-3.42938pt" id="M1" height="11.7782pt" version="1.1" viewBox="-0.0498162 -8.34882 18.973 11.7782"><g transform="matrix(.013,0,0,-0.013,0,0)"><path id="g113-113" d="M570 304C570 398 525 448 414 448C385 448 343 445 312 434L329 511L321 518C297 504 262 482 244 460L233 411C195 397 159 381 128 358L135 332C160 347 189 360 224 373L111 -147C97 -210 84 -218 17 -231L13 -257L254 -247L259 -218L233 -216C183 -212 177 -202 189 -142L218 -1C238 -10 266 -12 283 -12C351 3 429 48 483 105C543 168 570 242 570 304ZM482 289C482 161 380 33 304 33C278 33 248 51 233 69L303 396C326 400 352 403 369 403C428 403 482 380 482 289Z"/></g><g transform="matrix(.013,0,0,-0.013,11.342,0)"><path id="g117-91" d="M512 -3V55L134 254V256L512 456V514L75 281V230L512 -3Z"/></g></svg><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="28.184pt" style="vertical-align:-3.42938pt" height="11.7782pt" version="1.1" viewBox="22.555183800000002 -8.34882 28.184 11.7782"><g transform="matrix(.013,0,0,-0.013,22.605,0)"><path id="g113-49" d="M241 635C89 635 35 457 35 312C35 153 89 -12 240 -12C390 -12 443 166 443 312C443 466 390 635 241 635ZM238 602C329 602 354 454 354 312C354 172 330 22 240 22C152 22 124 173 124 313S148 602 238 602Z"/></g><g transform="matrix(.013,0,0,-0.013,28.845,0)"><path id="g113-47" d="M113 -12C146 -12 170 11 170 46C170 78 146 103 114 103S58 78 58 46C58 11 82 -12 113 -12Z"/></g><g transform="matrix(.013,0,0,-0.013,31.809,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,38.049,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,44.289,0)"><path id="g113-50" d="M384 0V27C293 34 287 42 287 114V635C232 613 172 594 109 583V559L157 557C201 555 205 550 205 499V114C205 42 199 34 109 27V0H384Z"/></g></svg>) and phenylalanine (<svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="18.973pt" style="vertical-align:-3.42938pt" id="M2" height="11.7782pt" version="1.1" viewBox="-0.0498162 -8.34882 18.973 11.7782"><g transform="matrix(.013,0,0,-0.013,0,0)"><use xlink:href="#g113-113"/></g><g transform="matrix(.013,0,0,-0.013,11.342,0)"><path id="g117-34" d="M535 323V373H52V323H535ZM535 138V188H52V138H535Z"/></g></svg><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="28.184pt" style="vertical-align:-3.42938pt" height="11.7782pt" version="1.1" viewBox="22.555183800000002 -8.34882 28.184 11.7782"><g transform="matrix(.013,0,0,-0.013,22.605,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,28.845,0)"><use xlink:href="#g113-47"/></g><g transform="matrix(.013,0,0,-0.013,31.809,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,38.049,0)"><path id="g113-53" d="M456 178V225H360V632H320C217 496 115 347 20 206V178H280V106C280 40 276 34 189 27V0H445V27C364 34 360 39 360 106V178H456ZM280 225H82C149 335 214 431 278 520H280V225Z"/></g><g transform="matrix(.013,0,0,-0.013,44.289,0)"><path id="g113-58" d="M244 635C114 635 38 519 38 422C38 317 111 240 217 240C236 240 255 244 277 256L345 292C311 140 203 39 59 15L64 -15C89 -15 150 -5 204 17C339 72 440 202 440 386C440 521 368 635 244 635ZM228 602C326 602 352 479 352 390C352 370 351 347 348 324C327 308 293 296 258 296C174 296 124 369 124 458C124 517 152 602 228 602Z"/></g></svg>), which were higher in the negative group. CSF TAU and P-TAU were significantly correlated with medium and small HDL in the negative group, and with extremely large VLDL in the positive group. Our results also indicated significant correlations of metabolites including unsaturated fatty acids, glycerol, and leucine with CSF core biomarkers. Conclusion. Based on our findings, a number of lipoproteins and metabolites were associated with CSF core biomarkers of AD. These correlations showed some differences in Apo-E ε4 positive and negative groups, which reminds the role of Apo-E gene status in the pathophysiology of AD development. However, further research is warranted to explore the exact association of lipoproteins and other metabolites with AD core biomarkers and pathology.

Azam Sajjadi Nasab

Fatemeh Noorani

Zahra Paeizi

Leila Khani

Saba Banaei

Mohammad Sadeghi

Melika Shafeghat

Mahan Shafie

Mahsa Mayeli

The Alzheimer's Disease Neuroimaging Initiative (ADNI)

A Comprehensive Investigation of the Potential Role of Lipoproteins and Metabolite Profile as Biomarkers of Alzheimer’s Disease Compared to the Known CSF Biomarkers

Alzheimer’s disease (AD) is a neurodegenerative condition that is pathologically characterized by the presence of amyloid plaques and neurofibrillary tangles. Animal models of AD have been useful in understanding the disease process and in investigating the effects of compounds on pathology and behavior. APP/PS1 mice develop amyloid plaques and show memory impairment. Cyclic glycine-proline (cGP) is a cyclic dipeptide that is likely produced from a tripeptide, glycine-proline-glutamate, which itself is generated after proteolytic cleavage of insulin-like growth factor-1. Here, we show that cGP improves spatial memory and reduces amyloid plaque burden in APP/PS1 mice. The results thus suggest that cGP could potentially provide beneficial effects in AD.

Tushar Arora

Shiv K. Sharma

Cyclic Glycine-Proline Improves Memory and Reduces Amyloid Plaque Load in APP/PS1 Transgenic Mouse Model of Alzheimer’s Disease

Background. According to recent studies, amyloid-β (Aβ) isoforms as cerebrospinal fluid (CSF) biomarkers have remarkable predictive value for cognitive decline in the early stages of Alzheimer’s disease (AD). Herein, we aimed to investigate the correlations between several targeted proteomics in CSF samples with Aβ ratios and cognitive scores in patients in AD spectrum to search for potential early diagnostic utility. Methods. A total of 719 participants were found eligible for inclusion. Patients were then categorized into cognitively normal (CN), mild cognitive impairment (MCI), and AD and underwent an assessment of Aβ and proteomics. Clinical Dementia Rating (CDR), Alzheimer’s Disease Assessment Scale (ADAS), and Mini Mental State Exam (MMSE) were used for further cognitive assessment. The Aβ42, Aβ42/Aβ40, and Aβ42/38 ratios were considered as means of comparison to identify those peptides corresponding significantly to these established biomarkers and cognitive scores. The diagnostic utility of the IASNTQSR, VAELEDEK, VVSSIEQK, GDSVVYGLR, EPVAGDAVPGPK, and QETLPSK was assessed. Results. All investigated peptides corresponded significantly to Aβ42 in controls. In those with MCI, VAELEDEK and EPVAGDAVPGPK were significantly correlated with Aβ42 (<svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-3.42943pt" id="M1" height="10.2124pt" version="1.1" viewBox="-0.0498162 -6.78297 7.83752 10.2124" width="7.83752pt"><g transform="matrix(.013,0,0,-0.013,0,0)"><path id="g113-113" d="M570 304C570 398 525 448 414 448C385 448 343 445 312 434L329 511L321 518C297 504 262 482 244 460L233 411C195 397 159 381 128 358L135 332C160 347 189 360 224 373L111 -147C97 -210 84 -218 17 -231L13 -257L254 -247L259 -218L233 -216C183 -212 177 -202 189 -142L218 -1C238 -10 266 -12 283 -12C351 3 429 48 483 105C543 168 570 242 570 304ZM482 289C482 161 380 33 304 33C278 33 248 51 233 69L303 396C326 400 352 403 369 403C428 403 482 380 482 289Z"/></g></svg> value < 0.001). Additionally, IASNTQSR, VVSSIEQK, GDSVVYGLR, and QETLPSK were significantly correlated with Aβ42/Aβ40 and Aβ42/38 (<svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-3.42943pt" id="M2" height="10.2124pt" version="1.1" viewBox="-0.0498162 -6.78297 7.83752 10.2124" width="7.83752pt"><g transform="matrix(.013,0,0,-0.013,0,0)"><use xlink:href="#g113-113"/></g></svg> value < 0.001) in this group. This group of peptides similarly corresponded to Aβ ratios in those with AD. Eventually, IASNTQSR, VAELEDEK, and VVSSIEQK were significantly associated with CDR, ADAS-11, and ADAS-13, particularly in MCI group. Conclusion. Our research suggests potential early diagnostic and prognostic utilities for certain peptides extracted from CSF-targeted proteomics research. The ethical approval of ADNI is available at ClinicalTrials.gov with Identifier: <a target="_blank" href="https://clinicaltrials.gov/ct2/show/NCT00106899">NCT00106899</a>.

Maryam Behzad

Negin Zirak

Ghazal Hamidi Madani

Linda Baidoo

Ali Rezaei

Shima Karbasi

Alzheimer’s Disease Neuroimaging Initiative

CSF-Targeted Proteomics Indicate Amyloid-Beta Ratios in Patients with Alzheimer’s Dementia Spectrum

Introduction. An Alzheimer’s disease (AD) dementia diagnosis is often preceded by an extended period of cognitive decline. Few studies have examined healthcare resource use (HRU) during an extended period before AD dementia diagnosis. Methods. In a historical claims-based cohort study, propensity score-matched cohorts of patients with and without AD dementia were observed for a 5-year prediagnosis period and a 1-year postdiagnosis period. Demographics, clinical characteristics, and HRU were compared between groups. Results. Individuals in the AD dementia group displayed a greater level of medical complexity in the year before diagnosis of AD dementia relative to those in the matched cohort. Both all-cause and AD dementia complication-related HRU increased gradually, with a marked spike at the time of initial AD dementia diagnosis. Discussion. Further research into the natural history of patients with AD dementia is necessary to improve identification of early AD and to better understand its broader impact.

Ibrahim M. Abbass

Dae Choi

Christopher Wallick

Sheila Seleri Assunção

Trends in Healthcare Resource Use Preceding Diagnosis of Alzheimer’s Disease Dementia

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International Journal of Alzheimer’s Disease publishes original research articles and&nbsp;review articles in all areas of Alzheimer's disease.

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International Journal of Alzheimer’s Disease | Hindawi

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International Journal of Alzheimer’s Disease publishes original research articles and review articles in all areas of Alzheimer's disease.

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International Journal of Alzheimer’s Disease

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International Journal of Alzheimer’s Disease