Can a Blood Test Predict Alzheimer’s disease?by Dario Dieguez, Jr, PhD | May 25, 2014
Alzheimer’s disease (AD) is an irreversible brain disease that causes progressive dementia. It currently affects over 35 million people worldwide and is expected to affect 115 million by 2050. A recent report indicates that AD claimed over 503,000 lives in Americans aged 75 and older in 2010. Abnormal changes in the brain are thought to begin several years prior to behavioral manifestations of the disease. This extended “pre-clinical phase” of AD represents a unique window of opportunity for therapeutic intervention.
However, at present, there are no known cures or therapies that can reduce the abnormal brain changes associated with AD (amyloid plaques and neurofibrillary tangles). This is likely due, at least in part, to the inability to accurately diagnose AD prior to the emergence of marked behavioral changes and memory loss. The results of a new study offer hope that this may now be possible.
In the past two decades, remarkable progress has been made in the ability to detect biomarkers for early AD, including measurement of plaques and tangles in cerebrospinal fluid, structural and functional magnetic resonance imaging of the abnormal AD brain, and the recent use of brain amyloid imaging. However, these methods are of limited utility since they are either invasive, time consuming, or expensive. Therefore, identification of useful blood-based biomarkers for pre-clinical AD would be ideal to facilitate the development of disease-modifying or preventative therapies.
A study led by Howard J. Federoff, M.D., Ph.D., Executive Vice President for Health Sciences, Executive Dean, and Professor of Neurology at Georgetown University Medical Center, has accomplished just that. The study, conducted in a collaboration among investigators at Georgetown University, University of Rochester School of Medicine, Unity Health System, Rochester General Hospital, University of California at Irvine, Temple University School of Medicine, and Regis University School of Pharmacy, was published in the April 2014 issue of Nature Medicine.
The researchers followed 525 study participants as part of the Rochester/Orange County Aging Study over the course of the 5-year observational study period. All participants were community-dwelling adults living in the Rochester, NY and Irvine, CA communities. For inclusion in the study, participants had to be aged 70 or older, proficient with written and spoken English, and have corrected vision and hearing necessary to complete the battery of cognitive tests.
Individuals who fulfilled any of the following conditions were excluded from the study: presence of major psychiatric or neurological disorders (including AD, stroke, epilepsy, or psychosis) at the time of study enrollment, current or recent use of anticonvulsants, neuroleptics, highly active antiretroviral therapy, antiemetics, or antipsychotics, or presence of any serious blood diseases. All study participants underwent an annual blood test and an annual battery of tests to assess five cognitive domains, including attention, executive function, language, memory, and visuospatial perception. Results of all cognitive tests were adjusted for age, sex, education, and visit.
Classification of study participants as part of either the amnesic mild cognitive impairment or mild AD (aMCI/AD) or normal control group was based on measures of memory performance. The normal control group included participants who matched those in the aMCI/AD group for age, sex, and education. Over the course of the study, 74 participants met criteria for aMCI/AD. Of these, 46 were incidental cases upon study entry and 28 converted from non-impaired memory to aMCI/AD (“Converters”) during the study. The average time for such conversion was 2.1 years.
In the third year of the study, 53 participants with either aMCI or AD (including 18 Converters) were selected to participate in the blood biomarker discovery studies. An additional 41 participants, consisting of the remaining 21 participants in the aMCI/AD group (including 10 Converters), and 20 matched NC participants, were included in subsequent validation studies. Remarkably, a panel of ten lipids in the blood were found to be at significantly lower levels in those destined to become Converters (previously described above), as compared to that in normal participants, predicted conversion (from normal) to either aMCI or AD within a two to three year timeframe with 90% accuracy.
These lipids normally function to provide structural and functional support to normal cell membranes (the outer, protective layers of cells). Therefore, reduced levels of these ten lipids in the blood may represent a breakdown of normal cell membrane integrity in participants destined to acquire aMCI or AD. In addition, they may mark the transition period from normal to aMCI or AD when abnormal changes in the brain may first become associated with changes in memory.
“We consider our results a major step towards the commercialization of a preclinical disease biomarker test that could be useful for large-scale screening to identify individuals at risk for AD,” said Dr. Federoff.
“If successful, it would be a major step in assisting the pharmaceutical industry in producing disease-modifying therapies at both early and late preclinical stages of dementia,” said Gisele Wolf-Klein, M.D., Director of Geriatric Education at North Shore-LIJ Health System, who was not involved in the study.
Hulstaert F, Blennow K, Ivanoiu A, Schoonderwaldt HC, Riemenschneider M, De Deyn PP, Bancher C, Cras P, Wiltfang J, Mehta PD, Iqbal K, Pottel H, Vanmechelen E, & Vanderstichele H (1999). Improved discrimination of AD patients using beta-amyloid(1-42) and tau levels in CSF. Neurology, 52 (8), 1555-62 PMID: 10331678
James BD, Leurgans SE, Hebert LE, Scherr PA, Yaffe K, & Bennett DA (2014). Contribution of Alzheimer disease to mortality in the United States. Neurology, 82 (12), 1045-50 PMID: 24598707
Klunk WE, Engler H, Nordberg A, Wang Y, Blomqvist G, Holt DP, Bergström M, Savitcheva I, Huang GF, Estrada S, Ausén B, Debnath ML, Barletta J, Price JC, Sandell J, Lopresti BJ, Wall A, Koivisto P, Antoni G, Mathis CA, & Långström B (2004). Imaging brain amyloid in Alzheimer’s disease with Pittsburgh Compound-B. Annals of neurology, 55 (3), 306-19 PMID: 14991808
Mapstone M, Cheema AK, Fiandaca MS, Zhong X, Mhyre TR, Macarthur LH, Hall WJ, Fisher SG, Peterson DR, Haley JM, Nazar MD, Rich SA, Berlau DJ, Peltz CB, Tan MT, Kawas CH, & Federoff HJ (2014). Plasma phospholipids identify antecedent memory impairment in older adults. Nature medicine, 20 (4), 415-8 PMID: 24608097
McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack CR Jr, Kawas CH, Klunk WE, Koroshetz WJ, Manly JJ, Mayeux R, Mohs RC, Morris JC, Rossor MN, Scheltens P, Carrillo MC, Thies B, Weintraub S, & Phelps CH (2011). The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s & dementia : the journal of the Alzheimer’s Association, 7 (3), 263-9 PMID: 21514250
Small SA, Perera GM, DeLaPaz R, Mayeux R, & Stern Y (1999). Differential regional dysfunction of the hippocampal formation among elderly with memory decline and Alzheimer’s disease. Annals of neurology, 45 (4), 466-72 PMID: 10211471
Sperling RA, Aisen PS, Beckett LA, Bennett DA, Craft S, Fagan AM, Iwatsubo T, Jack CR Jr, Kaye J, Montine TJ, Park DC, Reiman EM, Rowe CC, Siemers E, Stern Y, Yaffe K, Carrillo MC, Thies B, Morrison-Bogorad M, Wagster MV, & Phelps CH (2011). Toward defining the preclinical stages of Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s & dementia : the journal of the Alzheimer’s Association, 7 (3), 280-92 PMID: 21514248
Thambisetty M, & Lovestone S (2010). Blood-based biomarkers of Alzheimer’s disease: challenging but feasible. Biomarkers in medicine, 4 (1), 65-79 PMID: 20387303
World Health Organization. Dementia: A Public Health Priority (World Health Organization, Geneva, 2012).
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