Anti-Aging Therapeutics Volume XVI. A4M American Academy. Читать онлайн. Newlib. NEWLIB.NET

Автор: A4M American Academy
Издательство: Ingram
Серия:
Жанр произведения: Медицина
Год издания: 0
isbn: 9781934715178
Скачать книгу
measures (e.g., TOVA and CNSM) validate brain HM with clinically useful sensitivity and specificity. The P300 latency was significantly longer and the amplitude was significantly lower in the HM compared to the NM group, and these effects were retained after age correction. Neurocognitive measures (e.g., the MMSE [p=.01], TOVA [p=.00006], and CNSM [p=.0001] scores) were also significantly lower in the HM compared to the NM group. NM/HM compared to non-impaired/impaired CNSM were significant (p=.003), with more HM patients presenting poor memory than patients with NM.

      It also appears that patients with single-domain cognitive decline have less progression to dementia, followed by those who are multi-domain amnestic or non-amnestic, causing the use of electrophysiology to deteriorate.29,47,48 As MCI atrophy sets in and advances to dementia, positive hypometabolic FDG PET scans are helpful indicators. Brain metabolism then creates a cognitive tipping point that is indicative of dementia or AD.31 Our subjects, although incompletely characterized, had MCI by a series of neuropsychological measures. Current characterizations suggest that MCI needs greater stratification considering the many patients who already have features of dementia. Most patients with hypometabolic FDG PET scans do have early dementia, even if their current symptoms resemble only MCI.15

      MCI is heterogeneous, with electrophysiological decline, memory and attention failure, multiple domains of cognitive deterioration with and without losses of hippocampal volume, and cortical atrophy steering patients from MCI into dementia. There are numerous clinical variants of MCI that are antecedents to dementia, where progression is altered dependent on different cognitive phenotypes (e.g., individuals who emphasize working memory vs. auditory memory, abstract IQ vs. emotional IQ).49 A similar progression occurs in heart disease based on risk factors (e.g., cholesterol [HDL/LDL], electrophysiological dysfunction, valve and coronary artery disease, hormonal and vascular factors) which may occur in any combination dependent on genetic predispositions or environmental factors. Although no one system is perfectly predictive, an in-office model has been implemented, where electrophysiological decline, particularly, delays of processing speeds when moving from thought to action (e.g., TOVA and P300) seem to be validating PET hypometabolism.

      CONCLUDING REMARKS

      A significant rise in AD is expected with a continuing demographic shift to a more elderly population. AD is predicted to increase from 4.5 million in 2000 to 13.2 million in 2050 as Baby Boomers age and life expectancy increases.50 If primary care practices implement proper MCI checklists, P300, and TOVA testing done within an hour’s time, physicians will be able to diagnose early MCI antecedents.51-55 Sustaining our intellectual faculties with age may be possible with early diagnosis and treatment. These practices may also have economic advantages as a patient can receive the MCI domain assessment, electrophysiological markers and brain testing at a cost-effective price of $500, while PET scans still remain at an expensive price of $3000-6000 per patient. This proposal may aid in lessening the United States’ $200 billion dementia burden by identifying high-risk patients through multiple domains (e.g., P300 low voltage and slow speed and temporal differences between thought and action).56 These clinical implications may potentially impact the epidemic of dementia at a primary care level, similar to the ways an electrocardiography (ECG), cholesterol testing (HDL/LDL), and the echocardiogram lessened the cardiac burden worldwide.

      Future work confirming this clinically relevant research may indeed provide sufficient evidence to suggest the incorporation of impaired electrophysiological and neuropsychological determinants as an efficient means for identifying and validating reduced brain metabolism and cognitive impairment in MCI care settings leading to an early hallmark identifier of patient progression to dementia. We must await further studies before any real interpretation can be garnished from this important preliminary study.

      ACKNOWLEDGEMENTS

      The following individuals researched relevant literature, conducted statistical analysis, and/or assisted with manuscript revisions: Kenneth R. Perrine, Ph.D. (Weill Cornell Medical College), Vivian Lau, Mona Li, Raquel Lohmann, Pooja Reddy, Pavan Reddy, and Swetha Yeldandi.

      REFERENCES

      1.Alzheimer’s Association. Alzheimer’s disease facts and figures. Alzheimers Dement. 2010;6:158-194.

      2.Doody RS, Ferris SH, Salloway S, et al. Identifying Amnestic Mild Cognitive Impairment in Primary Care: A Feasibility Study. Clin Drug Investig. 2011;31:483-491.

      3.Alzheimer’s Association. Alzheimer’s disease facts and figures. Alzheimers Dement. 2011;7:48-52.

      4.Quiroz YT, Ally BA, Celone K, et al. Event-related potential markers of brain changes in preclinical familial Alzheimer disease. Neurology. 2011;77:469-475.

      5.van Rossum IA, Vos SJB, Knol DL, et al. Injury markers predict time to dementia in subjects with MCI and amyloid pathology. Neurology. 2012;79:1809-1816.

      6.Dlugaj M, Gerwig M, Wege N, et al. Elevated levels of high-sensitivity C-reactive protein are associated with mild cognitive impairment and its subtypes: results of a population-based case-control study. J Alzheimers Dis. 2012;28:503-514.

      7.Apostolova LG, Thompson PM, Green AE, et al. 3D Comparison of low, intermediate, and advanced hippocampal atrophy in MCI. Human Brain Mapping. 2010;31:786-797.

      8.Kim SH, Seo SW, Yoon DS, et al. Comparison of neuropsychological and FDG-PET findings between early- versus late-onset mild cognitive impairment: A five-year longitudinal study. Dement Geriatr Cogn Disord. 2010;29:213-223.

      9.Herholz K, Westwood S, Haense C, Dunn G. Evaluation of a calibrated (18)F-FDG PET score as a biomarker for progression in Alzheimer Disease and Mild Cognitive Impairment. J Nucl Med. 2011;52:1218-1226.

      10.Aisen PS, Petersen RC, Donohue MC, et al. Clinical core of the Alzheimer’s disease neuroimaging initiative: progress and plans. Alzheimers Dement. 2010;6:239-246.

      11.Silbert LC, Dodge HH, Perkins LG, et al. Trajectory of white matter hyperintensity burden preceding mild cognitive impairment. Neurology. 2012;79:741-747.

      12.Folstein MF, Folstein SE, McHugh PR. Mini-mental state: A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12:189-198.

      13.Woo BK, Harwood DG, Melrose RJ, et al. Executive deficits and regional brain metabolism in Alzheimer's disease. Int J Geriatr Psychiatry. 2010;25:1150-1158.

      14.Liepelt I, Reimold M, Maetzler W, et al. Cortical Hypometabolism Assessed by a Metabolic Ratio in Parkinson’s Disease Primarily Reflects Cognitive Deterioration – [18F]FDG-PET. Mov Disord. 2009;24:1504-1511.

      15.Koivunen J, Scheinin N, Virta JR, et al. Amyloid PET imaging in patients with mild cognitive impairment: A 2-year follow-up study. Neurology. 2011;76:1085-1090.

      16.Braverman ER, Chen TJ, Schoolfield J, et al. Delayed P300 latency correlates with abnormal Test of Variables of Attention (TOVA) in adults and Predicts Early Cognitive Decline in a Clinical Setting. Advances in Therapy. 2006;23:582-600.

      17.Braverman ER, Blum K. P300 (Latency) Event Related Potential: An Accurate Predictor of Memory Impairment. Clin Electroencephalogr. 2003;34:124-139.

      18.Del Sole A, Clerici F, Chiti A, et al. Individual cerebral metabolic deficits in Alzheimer's disease and amnestic mild cognitive impairment: an FDG PET study. Eur J Nucl Med Mol Imaging. 2008;35:1357-1366.

      19.Penny WE, Friston KJ, Ashburner JT, Kiebel SJ, Nichols TE. Statistical Parametric Mapping: The analysis of functional brain images. Burlington, MA: Elsevier;2007.

      20.Frank AR, Petersen R. Mild cognitive impairment. Handb Clin Neurol. 2008;89:217-221.

      21.Negash S, Geda YE, Petersen RC. Neuropsychological characterization of mild cognitive impairment. Handb Clin Neurol. 2008;88:499-509.

      22.Jackson CE, Snyder PJ. Electroencephalography and event-related potentials as biomarkers of mild cognitive impairment and mild Alzheimer's disease. Alzheimers Dement. 2008;4:137-143.

      23.Van Deursen JA, Vuurman EF, Smits LL, Verhey FR, Riedel WJ. Response speed, contingent negative variation