Asymmetric Insular Function Predicts Positional Blood Pressure in Nondemented Elderly
2009; American Psychiatric Association Publishing; Volume: 21; Issue: 2 Linguagem: Inglês
10.1176/jnp.2009.21.2.173
ISSN1545-7222
AutoresDonald R. Royall, Jia‐Hong Gao, Xia Zhao, Marsha J. Polk, Dean L. Kellogg,
Tópico(s)Spatial Neglect and Hemispheric Dysfunction
ResumoBack to table of contents Previous article Next article REGULARFull AccessAsymmetric Insular Function Predicts Positional Blood Pressure in Nondemented ElderlyDonald Royall M.D.Jia-Hong Gao Ph.D.Xia Zhao Ph.D.Marsha J. Polk M.Med.Dean Kellogg M.D.Donald Royall M.D.Jia-Hong Gao Ph.D.Xia Zhao Ph.D.Marsha J. Polk M.Med.Dean Kellogg M.D.Published Online:1 Apr 2009AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinked InEmail W e recently proposed that right insular dysfunction due to preclinical Alzheimer's disease or other neuropathology may mediate fall and syncope related morbidity and mortality in nondemented elderly. 1 This is predicated on our observation of a specific association between visuospatial cognitive measures and mortality in nondemented elderly retirees. 2 Similar tests are known to predict mortality in Alzheimer's disease, 3 while right hemisphere lesions are known to increase the risk of arrhythmic morbidity and mortality in stroke, 4 head injury, 5 and epilepsy. 6 Strokes that affect constructional tasks often involve the right insula as well. 7 Right insular stroke 8 or epileptic foci 9 often present with asystole. We hypothesize that preclinical Alzheimer's disease, which is known to affect the insular cortex at an early Braak stage, 10 is responsible for both our observed mortality in nondemented elderly retirees and "age-related" autonomic dysfunction in septuagenarians and octogenarians. 11 Our preliminary studies in press elsewhere 12 suggest that insular neurofibrillary tangle counts moderate the associations between both age, QT interval, and death. Forty percent of nondemented octogenarians have Braak stages consistent with insular involvement, and may be at risk. 13 In this study, we examine the association between right insular cerebral blood flow (rCBF) by perfusion MRI (pMRI) and measures of cardiovascular autonomic control, in nondemented retirees (Clinical Dementia Rating Scale score ≤1.0), 14 carefully screened to be free of comorbid cardiovascular disease. METHODSA convenience sample of 29 community dwelling elderly volunteers was tested with measures of cognition, autonomic function, and pMRI. Participants were recruited from noninstitutionalized levels of care in a for-profit San Antonio comprehensive care retirement community. After giving informed consent, participants were screened for diabetes, clinical ischemic heart and cerebrovascular disease by self-report, ECG, two dimensional echocardiography (2D-ECHO), and T2 weighted MRI. Resting insular rCBF was determined by pMRI. Forty-two subjects were recruited. However, 13 were eventually excluded due to abnormal ECG (n=5), a technically inadequate scan (n=2), intolerance of the pMRI (n=5), or on the basis of a Clinical Dementia Rating Scale score greater than 0.5 (n=1).NeuroimagingpMRI experiments were performed on a 1.9 T Elscint Prestige MRI scanner (Elscint Ltd., Haifa, Israel) at the Research Imaging Center of the University of Texas Health Science Center at San Antonio. Baseline images were used to rule out occult focal right hemisphere/insular cortical lesions as the cause of any constructional dyspraxia/autonomic dyscontrol. Any cases found to have either mass lesions or focal cortical infarctions/hemorrhagic lesions were excluded.Cerebral Blood Flow Absolute cerebral blood flow (CBF) was measured by dynamic contrast MRI using singular value decomposition with an adaptive threshold developed in our laboratory. 15 A single-shot multiple-slice spin Echo Planar Imaging pulse sequence was used with the following parameters: TR/TE/ =1500 msec/80 msec/90 (0), slice thickness =5 mm, and an in-plane spatial resolution of 3.3 mm by 3.3 mm. For each study, multiple-slices (120 images per slice) were obtained during a total scan time of 3 minutes. All subjects received 0.2 mmol/kg of a Gadolinium (Gd) based contrast agent (Magnevist, Berlex), delivered intravenously at a rate of about 5 ml/s into the antecubital vein. Injection of the contrast agent began 1.5 minutes after the start of the scan. The duration of the injection was approximately 4–6 sec. The tissue concentration time curve was calculated using the first 30 images after injection. The average signal of the 40 images prior to injection was used as the baseline signal. The arterial input function was determined in each subject from 4–6 pixels containing a large vessel, typically the middle cerebral artery. The CBF of both gray matter and white matter was determined using the procedure described in our previous publication. 15 White matter CBF does not decline with age, in contrast to gray matter CBF. 16 Cortical CBF was normalized to white matter CBF to offset intraindividual differences in absolute CBF. The left and right insular cortices were outlined in the T1 MRI image corresponding to the first EPI image from the perfusion scan time series (because of its high contrast). Then, the outlined regions of interest were registered to the regional CBF map obtained from our former calculation. The mean regional insular CBF values can be obtained by averaging the pixel values in its corresponding region of interest of the rCBF map. Because autonomic control is lateralized at the level of the insula, left hemisphere dominant asymmetry in the ratio of left:right insular cerebral blood flow (CBF) may define a group at relatively high risk for falls, syncope, or sudden death. Therefore, subjects were classified a priori into "high" and "low" risk groups on the basis of the ratio of their right:left insular rCBF. The high-risk group included individuals with left dominant (i.e., relatively low right) insular rCBF. Psychometric Measures Depressive symptoms were assessed using the 15-item short Geriatric Depression Scale. 17 – 18 Geriatric Depression Scale scores range from 0–15 and higher scores indicate a worse score. A cut-point of 6–7 best discriminates clinically depressed from nondepressed elderly. 19 The University of Pennsylvania Smell Identification Test (UPSIT) 20 was used to assess olfaction. The UPSIT is a standardized test of odor identification with good test-retest reliability (r=0.95) and strong correlation with detailed olfactory threshold tests (r=0.80). It contains 40 microencapsulated odors. The subject scratches and sniffs each test strip and chooses among multiple choices for the identity of each odor represented. The prompted design of a multiple-choice format minimizes the likelihood that UPSIT scores will be affected by verbal memory or executive impairments. UPSIT scores ≤ 18 indicate "anosmia" (e.g., severe odor identification deficits); scores of 19–33 (men) and 19–34 (women) indicate "microsmia." For this study, we assessed left and right nostril performance separately by asking the subject to close the contralateral nostril during UPSIT testing. The ratio of right:left UPSIT performance was then calculated. Cognitive MeasuresGeneral Cognition The Mini-Mental State Examination (MMSE) 21 is a well-known and widely used test for screening cognitive impairment. Scores range from 0–30, and a score of 28/30 is the median for normal octogenarians of greater than 12 years of education. 21 Scores below 24 reflect cognitive impairment. Memory Function The Connecticut Picture Learning Test (COPLT) 22 is a pictorial version of the California Verbal Learning Test. Subjects are asked to recall objects from a set of 16 line drawings of familiar objects (immediate recall), over five consecutive trials (COPLT total, maximum score of 80), after distraction (COPLT short, maximum score of 16) and after a 20 minute timed delay (COPLT long, maximum score of 16). The difference between the short delay trial and the fifth learning trial is COPLT retention (range=0−15). As in the COPLT, subjects taking the Rey Auditory Verbal Learning Task (RAVLT) 23 are asked to recall words from a 15-word list immediately (immediate recall), over five consecutive trials (RAV total, maximum score of 75), after distraction (RAV short, maximum score of 15), and after a 20-minute timed delay (RAV long, maximum score of 15). The difference between the short delay trial and the fifth learning trial is RAV retention (range=0–15). Executive Control An Executive Clock-Drawing Task 24 (CLOX) is a brief executive cognitive function measure based on a clock-drawing task. It is divided into two parts. CLOX1 is an unprompted task that is sensitive to executive control. CLOX2 is a copied version that is less dependent on executive skills. CLOX1 is more "executive" than several other comparable clock-drawing tasks. 25 Each CLOX subtest is scored on a 15-point scale. Lower CLOX scores are impaired. Cut-points of 10/15 (CLOX1) and 12/15 (CLOX2) represent the 5th percentiles for young-adult comparison subjects. The Executive Interview (EXIT25) 26 provides a standardized clinical executive cognitive function assessment. Items assess verbal fluency, design fluency, frontal release signs, motor/impulse control, imitation behavior, and other clinical signs associated with frontal system dysfunction. EXIT25 scores correlate well with other ECF measures including the Wisconsin Card Sorting Task (WCST) (r=−0.54), Trail Making Test Part B (r=0.64), Lezak's Tinker Toy test (r=−0.57), and the Test of Sustained Attention (Time, r=0.82; Errors, r=0.83). EXIT25 scores range from 0 to 50. High scores indicate impairment. A score of 10/50 reflects the 5th percentile for young adults. Scores ≥15/50 suggest clinically significant executive cognitive function dysfunction. Trail Making Test Part B 27 is a test of conceptualization, psychomotor speed, and attention. The subject draws lines to connect consecutively numbered circles on Trails A. Trails B requires the subject to connect consecutively numbered and lettered circles, alternating between the two sequences. The time in seconds to complete each task is recorded. Visuospatial Function CLOX2 and Trails A were used as foils to their more executive counterparts, CLOX1 and Trails B. In addition, we used the Weschler Adult Intelligence Scale—Revised (WAIS) Digit Symbol Coding. 28 The Digit Symbol Coding is a test of psychomotor speed and attentional control. The subject is asked to copy, as quickly as possible, nonsense symbols corresponding to specific numbers presented in a key at the top of the page. Cardiovascular Assessment Potential subjects with self-reported histories of diabetes, acute myocardial infarction, cerebrovascular accidents, valvular heart disease, or cardiothoracic surgery were excluded. Subjects without self-reported acute myocardial infarction or cerebrovascular accidents were further tested with resting electrocardiography (ECG) and T2 weighted MRI. Five subjects were excluded because of abnormal ECG findings, including silent acute myocardial infarction by ECG, greater than first degree heart block, bundle branch blocks, or atrial fibrillation. Subjects with supraventricular arrhythmias and/or first degree heart block were allowed. Potential subjects with any self-reported history of valvular disease or congestive heart disease were excluded. Echocardiography (2D ECHO) was obtained in a subset of cases with self-reported orthopnea/dyspnea on exertion. No subject had an abnormal left ventricular ejection fraction. At MRI, participants were screened for focal cortical lesions, or lacunar subcortical gray matter lesions. None were excluded on this basis. Subjects with "ischemic" periventricular white matter disease were allowed. Autonomic function in the remaining cases was assessed by ECG and 24 hour Holter monitoring. Mean p -r (PR) intervals and rate corrected Q-T intervals (QTc) were calculated from Holter records. Systolic blood pressures were assessed lying, sitting and standing, by mercury sphygmomanography, using a size appropriate cuff in the right upper extremity. Positional blood pressure changes (ΔSBP) were assessed by the difference between sitting and standing systolic blood pressures. Statistical AnalysesCross-group differences were tested by Student's t test, and Analysis of Variance (ANOVA). Associations between continuous variables were tested by parametric correlations. Significant univariate correlations were adjusted in multiple regression models. Because of the small sample size, regression models were limited to one covariate.RESULTSLeft and right insular rCBF were highly intercorrelated (r=0.97, p<0.001). Each was also strongly correlated with both total white matter and frontal cortical rCBF (r=0.80–0.83, p<0.001 in all cases). Mean resting insular rCBF was significantly higher on the right (t test for dependent samples: t=2.5, p=0.02) and the ratio of right:left insular rCBF was skewed in favor of right insular dominance. On the other hand, 10/29 participants (34.5%) had left dominant rCBF and were assigned to the theoretically "high" risk group, defined by relatively low right insular rCBF. Clinical data, stratified by "risk" group, are presented in Table 1 . There were no differences in left insular, frontal or white matter rCBF across high/low risk groups. In contrast, right insular rCBF was significantly lower in high-risk group (F=6.5, df=1, 28, p=0.01). The ratio of right insular to frontal rCBF was significantly lower in the high-risk group (t=−2.54, df=27, p=0.017). There was no difference in the ratio of left insular to frontal rCBF. Similarly, the ratio of right insular to total white matter rCBF was significantly lower in the high-risk group (t=−2.86, df=27, p<0.01). There was no difference in the ratio of left insular to total white matter rCBF. These findings suggest an absolute reduction in right insular rCBF in high-risk cases. TABLE 1. Clinical Characteristics by Risk GroupTABLE 1. Clinical Characteristics by Risk GroupEnlarge table The high-risk group also had a greater positional drop in blood pressure (F=4.9, df=1, 27, p=0.04) ( Figure 1 ). There were no cross-group differences with regard to resting heart rate, mean 24 hour P-R interval, or mean 24 hour rate corrected Q-T interval. The high-risk group was significantly younger (t=−2.39, df=27, p=0.02), and had fewer depressive symptoms on the Geriatric Depression Scale (t=−2.24, df=26, p=0.03). Neither group approached the threshold for clinically significant Geriatric Depression Scale scores. High-risk subjects performed significantly better on the COPLT (short: t=2.95, df=22, p=0.01; long: t=2.44, df=22, p=0.02), but not the RAVLT. The high-risk group also performed less well on Trails A (t=−2.15, df=27, p=0.04). There were no cross-group differences on measures of general cognition (MMSE) or executive function (CLOX1, EXIT25, Trails B) and the mean scores were in the normal range on all of these measures. Positional blood pressure change was significantly associated with memory, as measured by the COPLT (total: r=−0.44, p<0.05; short: r=−0.49, p<0.05; long: r=−0.44, p<0.05). However, these associations were all inverse, suggesting that positional drops in blood pressure were associated with better memory performance. These associations resisted adjustment for age. However, no memory measure predicted positional blood pressure change after adjusting for right:left insular rCBF (nonsignificant), suggesting that asymmetric insular function mediates their association. Positional blood pressure change was not significantly correlated with RAVLT scores, CLOX1, CLOX2, DSS, EXIT25, MMSE, Trails A/B, or UPSIT scores. The ratio of right:left insular rCBF was also significantly associated with COPLT and not RAVLT performance, (COPLT total: r= −0.46, p<0.01; COPLT short: r= −0.68, p right insular rCBF, and absolute reductions in right insular rCBF. These changes can be demonstrated in the absence of dementia. Although these data cannot address the cause of these asymmetries in insular rCBF, preclinical Alzheimer's disease pathology is endemic in the nondemented elderly, involves the insula, and is likely to be unilateral in its earlier stages.Received July 24, 2007; revised December 21, 2007, and January 25, 2008; accepted January 31, 2008. Drs. Royall and Polk are affiliated with the Department of Psychiatry at The University of Texas Health Sciences Center at San Antonio and the South Texas Veterans Health Administration Geriatric Research Education and Clinical Center (GRECC); Drs. Royall and Kellogg are affiliated with the Department of Medicine at The University of Texas Health Sciences Center at San Antonio, and the South Texas Veterans Health Administration GRECC; Dr. Royall is also affiliated with the Departments of Medicine and Pharmacology at The University of Texas Health Sciences Center at San Antonio; Drs. Gao and Zhao are affiliated with the Department of Radiology and Research Imaging Center at The University of Texas Health Sciences Center at San Antonio. Address correspondence to Dr. Donald Royall, Department of Psychiatry, The University of Texas Health Science Center, 7703 Floyd Curl Dr., Mail code: 7792, San Antonio, TX 78229-3900; [email protected] (e-mail).Copyright © 2009 American Psychiatric Publishing, Inc.References1. Royall DR, Gao J-H, Kellogg DL Jr: Insular Alzheimer's disease pathology as a cause of "age-related" autonomic dysfunction and mortality in the non-demented elderly. Med Hypotheses 2006; 67:747–758Google Scholar2. Royall DR, Mouton C, Chiodo LK, et al: Cognitive predictors of mortality in elderly retirees: results from the Freedom House study. Am J Geriatr Psych 2007; 15:243–251Google Scholar3. Claus JJ, Walstra GJ, Bossuyt PM, et al: A simple test of copying ability and sex define survival in patients with early Alzheimer's disease. Psychol Med 1999; 29:485–489Google Scholar4. Orlandi G, Fanucchi S, Strata G, et al: Transient autonomic nervous system dysfunction during hyperacute stroke. Acta Neurologica Scand 2000; 102:317–321Google Scholar5. Rapenne T, Moreau D, Lenfant F, et al: Could heart rate variability predict outcome in patients with severe head injury? A pilot study. J Neurosurg Anesthesiol 2001; 13:260–268Google Scholar6. Hilz MJ, Dutsch M, Perrine K, et al: Hemispheric influence on autonomic modulation and baroreflex sensitivity. Ann Neurol 2001; 49:575–584Google Scholar7. Kertesz A, Harlock W, Coates R: Computer tomographic localization, lesion size, and prognosis in aphasia and nonverbal impairment. Brain Lang 1979; 8:34–50Google Scholar8. Aszalos Z, Barsi P, Vitrai J, et al: Lateralization as a factor in the prognosis of middle cerebral artery territorial infarct. Eur Neurol 2002; 48:141–145Google Scholar9. Howell SJ, Blumhardt LD: Cardiac asystole associated with epileptic seizures: a case report with simultaneous EEG and ECG. J Neurol Neurosurg Psychiatry 1989; 52:795–798Google Scholar10. Braak H, Braak E: Neuropathological staging of Alzheimer-related changes. Acta Neuropath 1991; 82:239–259Google Scholar11. Royall DR, Gao JH, Kellogg DL Jr: Insular Alzheimer's disease pathology as a cause of "age-related" autonomic dysfunction and mortality in the non-demented elderly. Med Hypotheses 2006; 67:747–758Google Scholar12. Royall DR: Insular Alzheimer's disease pathology and the psychometric correlates of mortality. Cleve Clin J Med 2008; 75(suppl 2):S97–99Google Scholar13. Braak H, Braak E: Evolution of neuronal changes in the course of Alzheimer's disease. J Neural Transmission 1998; 53:127–140Google Scholar14. Hughes CP, Berg L, Danziger WL, et al: A new clinical scale for the staging of dementia. Br J Psychiatry 1982; 140:566–572Google Scholar15. Liu HL, Pu Y, Liu Y, et al: Cerebral blood flow measurement by dynamic contrast MRI using singular value decomposition with an adaptive threshold. Magn Reson Med 1999; 42:167–172Google Scholar16. Leenders KL, Perani D, Lammertsma AA, et al: Cerebral blood flow, blood volume and oxygen utilization: normal values and effect of age. Brain 1990; 113:27–47Google Scholar17. Sheikh JI, Yesavage JA: Geriatric Depression Scale (GDS): recent evidence and development of a shorter version. Clin Gerontologist 1986; 5:165–173Google Scholar18. Maixner SM, Burke WJ, Roccaforte WH, et al: A comparison of two depression scales in a geriatric assessment clinic. Am J Geriatr Psychiatry 1995; 3:60–67Google Scholar19. Gerety MB, Williams JW Jr, Mulrow CD, et al: Performance of case-finding tools for depression in the nursing home: influence of clinical and functional characteristics and selection of optimal threshold scores. J Am Geriatr Soc 1994; 42:1103–1109Google Scholar20. Doty RL: The Smell Identification Test™ Administration Manual. Philadelphia, Penn, Sensonics, Inc, 1983Google Scholar21. Folstein MF, Folstein SE, McHugh PR, et al: Mini-Mental State Examination User's Guide. Odessa, Fla, Psychological Assessment Resources, Inc, 2001Google Scholar22. Stevens MC, Fein DA, Markus E: Connecticut picture learning test: a pictorial version of the California Verbal Learning Test. Clin Neuropsychol 2001; 15:95–108Google Scholar23. Rey A: Mémorisation d'une série de 15 mots en 5 répétitions, in L'examen clinique en psychologie. Edited by Rey A. Paris, Presses Universitaires de France, 1958Google Scholar24. Royall DR, Cordes JA, Polk M: Clox: an executive clock drawing task. J Neurol, Neurosurg Psychiatry 1998; 64:588–594Google Scholar25. Royall DR, Mulroy A, Chiodo LK, et al: Clock drawing is sensitive to executive control: a comparison of six methods. J Gerontol B, Psychol Sci Soc Sci 1999; 54:P328–333Google Scholar26. Royall DR, Mahurin RK, Gray KF: Bedside assessment of executive cognitive impairment: the executive interview (EXIT). J Am Geriatr Soc 1992; 40:1221–1226Google Scholar27. Reitan RM: Validity of the Trail Making Test as an indicator of organic brain damage. Percept Motor Skills 1958; 8:271–276Google Scholar28. Wechsler D Wechsler Adult Intelligence Scale-Revised. New York, Psychological Corporation, 1991Google Scholar29. Mainardi LT, Bianchi AM, Cerutti S: Time-frequency and time-varying analysis for assessing the dynamic responses of cardiovascular control. Crit Rev Biomed Eng 2002; 30:175–217Google Scholar30. Winchell RJ, Hoyt DB: Spectral analysis of heart rate variability in the ICU: a measure of autonomic function. J Surg Res 1996; 63:11–16Google Scholar31. McShane RH, Nagy Z, Esiri MM, et al: Anosmia in dementia is associated with Lewy bodies rather than Alzheimer's pathology. J Neurol Neurosurg Psychiatry 2001; 70:739–743Google Scholar32. Tiraboschi P, Salmon DP, Hansen LA, et al: What best differentiates Lewy body from Alzheimer's disease in early-stage dementia? Brain 2006; 129:729–735Google Scholar33. Williams MM, Xiong C, Morris JC, et al: Survival and mortality differences between dementia with Lewy bodies vs Alzheimer disease. Neurology 2006; 67:1935–1941Google Scholar34. Weisman D, McKeith I: Dementia with Lewy bodies. Semin Neurol 2007; 27:42–47Google Scholar35. Geddes JW, Snowdon DA, Soultanian NS, et al: Braak stages III – IV of Alzheimer's related neuropathology are associated with mild memory loss. Stages V-VI are associated with dementia: findings from the Nun study. J Neuropathol Exp Neurol 1996; 55:617Google Scholar36. Kennedy SH, Evans KR, Kruger S, et al: Changes in regional brain glucose metabolism measured with positron emission tomography after paroxetine treatment of major depression. Am J Psychiatry 2001; 158:899–905Google Scholar37. Dazzan P, Morgan KD, Orr K, et al: Different effects of typical and atypical antipsychotics on grey matter in first episode psychosis: the Aesop study. Neuropsychopharmacology 2005; 30:765–774Google Scholar38. Ueda H, Kitabayashi Y, Narumoto J, et al: Relationship between Clock Drawing Test performance and regional cerebral blood flow in Alzheimer's disease: a single photon emission computed tomography study. Psychiatry Clin Neurosci 2002; 56:25–29Google Scholar39. Nagahama Y, Okina T, Suzuki N, et al: Neural correlates of impaired performance on the Clock Drawing Test in Alzheimer's disease. Dement Geriatr Cogn Disord 2005; 19:390–396Google Scholar40. Lye TC, Piguet O, Grayson DA, et al: Hippocampal size and memory function in the ninth and tenth decades of life: the Sydney older persons study. J Neurol Neurosurg Psychiatry 2004; 75:548–554Google Scholar41. Stern Y, Moeller JR, Anderson KE, et al: Different brain networks mediate task performance in normal aging and AD: defining compensation. Neurology 2000; 55:1291–1297Google Scholar FiguresReferencesCited byDetailsCited byThe Insular Cortex, Alzheimer Disease Pathology, and Their Effects on Blood Pressure Variability6 May 2020 | Alzheimer Disease & Associated Disorders, Vol. 34, No. 3 Volume 21Issue 2 Spring, 2009Pages 173-180 Metrics PDF download History Published online 1 April 2009 Published in print 1 April 2009
Referência(s)