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2012: Letters to the Editor by Month
January 2012 
January 2012
We would like to make you aware of follow-up clinical data from an open-label extension (OLE) study (AVA104617) to the rosiglitazone positron emission tomography (PET) study 49653/461, which was recently published [1]. The complex and technical nature of the PET study and the need to present results in a comprehensive fashion precluded the inclusion of these open-label data in the original manuscript. Therefore we are making the following information available to your readers.
Subjects who completed the 12-month, placebo-controlled, parent study were eligible to enter into this OLE study. All subjects entering the OLE study received an investigational formulation of rosiglitazone (RSG-XR) 4 mg for the first 4 weeks and then 8 mg for the remaining 44 weeks of the study. Study outcomes evaluation visits were conducted at 4 or 8-week intervals. The primary objective of the study was to evaluate the long-term safety and tolerability of RSG-XR. The secondary objective was to measure changes in cognition using the Mini-Mental Status Examiniation (MMSE). This OLE was conducted at 7 of the sites (6 in the US, 1 in Canada) that participated in the PET study.
Thirty-three subjects entered into the OLE and comprise the safety population. The mean age of the subjects who entered the study was 71.9 (9.75 SD), 55% were male, 94% were Caucasian, and 21 (64%) completed the 48 weeks of treatment. Of the 12 subjects who withdrew prematurely, 2 were withdrawn due to serious adverse events (pelvic fracture, fall and convulsion) and 2 were withdrawn due to non-serious adverse events. The remainder of subjects who withdrew prematurely did so mostly for non-specific reasons (n= 4) or a lack of efficacy/disease progression (n=3).
The most common adverse events (reported in > 5% of subjects [n=33]) are listed below:
n (%)
Any adverse event 25 (76)
Edema peripheral 4 (12)
Depression 3 (9)
Fall 3 (9)
Hematoma 2 (6)
Abnormal loss of weight 2 (6)
Vomiting 2 (6)
Agitation 2 (6)
Bursitis 2 (6)
There were no fatalities during the study. Clinical laboratory data indicated a mild decline in mean (SD) hemoglobin (n=13, 11.1(4.2) g/L) and hematocrit (n=13, 3.9(1.8) %) consistent with the known effects of rosiglitazone. There were no clinically significant changes noted on ECGs during the conduct of this study.
There were no specific concerns noted regarding cardiovascular safety; rates of events for myocardial ischemia was low (1/33, 3%).
Subjects entered the study with a mean MMSE at baseline of 17.4. During the conduct of this study, there was a mean decline in MMSE scores of 4.5 (4.1 SD) points which is consistent with the natural rate of disease progression [2].
In conclusion, this OLE study enrolled 33 subjects who completed study 49653/461 [1]. The subjects who enrolled in this OLE study were demographically similar to those who enrolled in the parent study. The safety data obtained during this study are consistent with the known side-effect profile of rosiglitazone. The small sample size, non-randomized population and lack of control group preclude any conclusions about the efficacy of rosiglitazone in this population.
Michael Gold1, Barbara Jeter2, Paul M. Mathews3
1Formerly of GlaxoSmithKline, currently of Allon Therapeutics, Vancouver, British Columbia
2GlaxoSmithKline, Neurosciences Medicine Development Centre, Research Triangle Park, NC, USA
3GlaxoSmithKline, Clinical Imaging Centre, Hammersmith Hospital, London, UK and Department of Clinical Neuroscience, Imperial College, London, UK
References
[1] Tzimopoulou S, Cunningham VJ, Nichols TE, Searle G, Bird NP, Mistry P, Dixon IJ, Hallett WA, Whitcher B, Brown AP, Zvartau-Hind M, Lotay N, Lai RY, Castiglia M, Jeter B, Matthews JC, Chen K, Bandy D, Reiman EM, Gold M, Rabiner EA, Matthews PM (2010) A multi-center randomized proof-of-concept clinical trial applying [18F]FDG-PET for evaluation of metabolic therapy with rosiglitazone XR in mild to moderate Alzheimer's disease. J Alzheimers Dis 22, 1241-1256.
[2] Doody R, Massman P, Dunn J (2011) A method for estimating progression rates in Alzheimer disease. Arch Neurol 58, 449-454.
December 2011
Response to “Possible alteration of amyloid precursor protein metabolism or trafficking in a 17 β-hydroxysteroid dehydrogenase X deficient patient”
We thank Dr. Xue-Ying He and collaborators for their interesting observations, which add important information to our work.
Regarding the nomenclature of the disease, we agree that “17β-hydroxysteroid dehydrogenase X deficiency”, or “HSD10 deficiency” as an alternative name, is the specific disorder of this patient. Although the type of 17β-hydroxysteroid dehydrogenase is not detailed in the title, “HSD10 deficiency” as the specific disease of the patient is largely stated all over the text. In any case, we agree that it should have been useful to clarify it in the title.
On the other hand, we fully agree with Dr. He and collaborators about the necessity of analyzing other varieties of amyloid-β peptides in the cerebrospinal fluid (CSF) and to confirm the results by other more complex procedures. We are grateful indeed for these suggestions. Unfortunately the CSF volume from this patient that still remains in our laboratory is probably not enough to carry out these complementary experiments. Nevertheless, it would be extremely useful to collect more CSF in future patients in order to validate, and make more complete, the reported results.
Carlos Ortez1,2, Cristina Villar1,2, Carmen Fons1,2, Sofía T. Duarte1,3, Ana Pérez1,2, Judith García-Villoria2,4, Antonia Ribes2,4, Aida Ormazábal2,5, Mercedes Casado2,5, Jaume Campistol2,5, Maria Antonia Vilaseca2,5, Angels García-Cazorla1,2
Department of 1Neurology and 5Biochemistry, Hospital Sant Joan de Déu, Barcelona, Spain
2CIBER-ER (Biomedical Network Research Centre on Rare Diseases), Instituto de Salud Carlos III, Madrid, Spain
3Neuropaediatric Department, Hospital D. Estefânia, CHLC, EPE and CEDOC, Faculdade de Ciências Médicas da Universidade Nova de Lisboa, Portugal
4Sección de Errores Congénitos del Metabolismo (IBC), Servicio de Bioquímica y Genética Molecular, Hospital Clínic, Barcelona, Spain.
Possible Alteration of Amyloid-β Protein Precursor Metabolism or Trafficking in a 17β-Hydroxysteroid Dehydrogenase X Deficiency Patient
We read with great interest the recent report by Ortez et al. [1], “Undetectable levels of CSF amyloid-β (Aβ) peptide in a patient with 17β-hydroxysteroid dehydrogenase deficiency”. The authors claim that Aβ peptide was not detectable in the cerebrospinal fluid (CSF) of a mentally retarded patient. The dramatically reduced levels of amyloid-β peptide in CSF might indicate an alteration of amyloid-β protein precursor metabolism or trafficking in the patient’s brain. To our knowledge, thirteen of fourteen different types of 17β-hydroxy-steroid dehydrogenase have been discovered in human tissues [2]. For example, 17β-hydroxysteroid dehydrogenase III deficiency [3] is a completely different disease from 17β-hydroxysteroid dehydrogenase X deficiency [4]. The disease suffered by this patient should be specifically described as “17β-hydroxysteroid dehydrogenase X deficiency” rather than 17β-hydroxysteroid dehydrogenase deficiency—an all-inclusive term.
A variety of amyloid-β peptides including Aβ1-37, Aβ1-38, Aβ1-39, Aβ1-40, and Aβ1-42 are present in human CSF [5]. However, data presented in this article (see Fig. 1 of Ref. 1) showed only the absence of a 44 kDa protein band in the patient’s CSF. As the authors emphasize, their finding points to a new direction for the study of Aβ metabolism, and it suggests that 17β-hydroxysteroid dehydrogenase X inhibitors might be candidates for Alzheimer’s disease therapy. Therefore, it is important that the absence of Aβ be firmly established. The masses of Aβ peptides lie in the range of 4300-4500 amu, and in several Western blotting procedures they migrate as monomers of apparent masses of about 4 kDa. Santa Cruz Biotechnology, Inc., the source of the antibody, claims that the band around 40 kDa revealed by their antibody is an oligomeric form of the 4 kDa peptide [6]; however, in experimental samples other explanations may account for the presence or absence of the band. We think that before one can accept that 17β-hydroxysteroid dehydrogenase X deficiency alters amyloid-β protein precursor metabolism or trafficking, the experiment must be repeated with other better characterized antibodies in other separation systems. For instance, a more sophisticated experimental procedure, namely quantitative urea-based Aβ-SDS-PAGE/immunoblot, could be employed [5]. We hope this patient will be demonstrated not to be an anecdotal case of the reduction of Aβ peptide levels in CSF. The finding could be confirmed in other HSD10 deficiency patients carrying the same mutation (c.628C>T) [7] or different mutations [8,9] in the HSD17B10 gene.
Xue-Ying He1, David Miller2, Song-Yu Yang1
Departments of 1Neurochemistry and 2Molecular Biology, NYS Institute for Basic research in Developmental Disabilities, Staten Island, NY, USA
Email: songyu.yang@csi.cuny.edu
Acknowledgments: This work was supported in part by the NYS Office for People With Developmental Disabilities.
References
[1] Ortez C, Villar C, Fons C, Duarte ST, Perez A, Garcia-Villopia J, Ribes A, Ormazabal A, Casado M, Campistol J, Vilaseca MA, Garcia-Cazorla A (2011) Undetectable levels of CSF amyloid-β peptide in a patient with 17β-hydroxysteroid dehydrogenase deficiency. J Alzheimers Dis 27, 253-257.
[2] Moeller G, Adamski J (2009) Integrated view on 17beta-hydroxysteroid dehydrogenase. Mol Cell Endocrinol 301, 7-19.
[3] Mains LM, Vakili B, Lacassie Y, Andersson S, Lindqvist A, Rock JA (2008) 17beta-hydroxysteroid dehydrogenase 3 deficiency in a male pseudoherma- phrodite. Fertil Steril 89, 228.e13-17.
[4] Yang SY, He XY, Miller D (2011) Hydroxysteroid (17beta) dehydrogenase X in human health and disease. Mol Cell Endocrinol 343, 1-6.
[5] Bibl M, Mollenhauer B, Esselmann H, Lewczuk P, Klafki H, Sparbier K, Smironov A, Cepek L, Trenkwalder C, Ruther E, Kornhuber J, Otto M, Wiltfang J (2006) CSF amyloid-β-peptides in Alzheimer’s disease, dementia with Lewy bodies and Parkinson’s disease dementia. Brain 129, 1177-1187.
[6] Liu RT, Zou LB, Fu JY, Lu QJ (2010) Effects of liquiritigenin treatment on the learning and memory deficits induced by amyloid β-peptide (25-35) in rats. Behavioural Brain Res 210, 24-31.
[7] García-Villoria J, Navarro-Sastre A, Fons C, Pérez-Cerdá C, Baldellou A, Fuentes-Castelló MA, González I, Hernández-Gonzalez A, Fernández C, Campistol J, Delpiccolo C, Cortés N, Messeguer A, Briones P, Ribes A (2009) Study of patients and carriers with 2-methyl-3-hydroxybutyryl-CoA dehydrogenase (MHBD) deficiency: difficulties in the diagnosis. Clin Biochem 1-2, 27-33.
[8] Seaver LH, He XY, Abe K, Cowan T, Enns GM. Sweetman L, Lee S, Malik M, Yang SY (2011) A novel mutation in the HSD17B10 gene of a 10-year-old boy with refractory epilepsy, chreoathetosis and learning disability. PLoS ONE 6, 11. e27348.
[9] Yang SY, He XY, Olpin SE, Sutton VR, McMenamin J, Philipp M, Denman RB, Malik M (2009) Mental retardation linked to mutations in the HSD17B10 gene interfering with neurosteroid and isoleucine metabolism. Proc Natl Acad Sci U S A 106, 14820-14824.
Response to Letter to the Editor from Anderson
We greatly appreciate the comment of Dr. George Anderson on our recently published paper in the Journal of Alzheimer’s Disease. Although we were aware of the fact that in Alzheimer’s disease and in major depression the circadian regulation is disturbed, we did not focus in this study on the role of circadian genes and the aryl hydrocarbon receptors in the regulation of indoleamine 2,3-dioxygenase (IDO). However, we were pleased to read Dr. Anderson’s remarks and discussion, and, indeed, it might be worthwhile including circadian aspects in future models of depression and Alzheimer’s disease.
Niki Dobos, Ulrich L. M. Eisel, Paul G. M. Luiten
Response to Article: Dobos N, de Vries FF, Kema IP, Patas K, OPrins M, Nijholt IM, Dierckx RA, Korf J, den Boer JA, Luiten PG, Eisel UL (2012) The role of indoleamine 2,3-dioxygenase in a mouse model of neuroinflammation-induced depression. J Alzheimers Dis, doi: 10.3233/JAD-2011-111097
I read with interest the recent article by Dobos et al. [1] on the role of indoleamine 2,3-dioxygenase (IDO) in depression (MDD), suggestive of overlaps to the role of IDO in Alzheimer’s disease (AD). The kynurenine pathways are an area of extensive current research, given the links to stress, prodromal MDD, emergent seizures, and neurodegeneration [2]. I wondered as to whether the authors had considered a role for the aryl hydrocarbon receptor (AHr) and circadian genes in the regulation of IDO.
Recent data suggests a significant role for the AHr in the induction of IDO in different cell types [3]. The AHr is activated by kynurenine [4], suggesting a possible positive feedback loop whereby IDO, or maybe more likely TDO (tryptophan 2,3-dioxygenase), induced kynurenine would activate the AHr, leading to IDO induction. In both MDD and AD, increased HPA axis activity enhances cortisol induction of TDO in astrocytes and some neurons. The release of kynurenine would then activate microglia AHr, leading to the induction of IDO and quinolinic acid (QA). QA is excitotoxic, increasing neuronal loss and contributing to emergent seizures [2]. QA is increased in some central nervous system regions in stress-induced depression in rodents [5] and in MDD patients [6]. Such a scenario suggests a powerful role for the intercommunication between glia, via the kynurenine pathway products, in the overlap of MDD and AD.
Circadian dysregulation is a relevant factor in both AD and mood disorders [7,8]. Circadian genes have a role in the regulation of the IDO pathways. The circadian gene Period1 is known to interact with, and modulate the activity of, the AHr [9]. TCDD, the classical activator of the AHr, shows dramatic differences between day and night AHr inductions [10]. If indeed the AHr is a significant inducer of IDO in microglia, some of the circadian gene and melatonin links to AD and MDD may be driving significant alterations in glia kynurenine pathway activity, with impacts on neuronal activity and survival.
There are likely many different facets and etiologies to MDD. Somatization significantly overlaps with MDD, and has been shown recently by Michael Maes and colleagues to be differentiated from MDD on the basis of the patterning of kynurenine pathway products [11]. Specifically somatization shows increased kynurenine and relatively decreased kynurenic acid in comparison to MDD. This could suggest that somatization is a confounding factor in conceptualizations of overlaps in the biochemical underpinnings of MDD and AD.
George Anderson
CRC, 57 Laurel Street, Scotland G11 7QT
anderson.george@rocketmail.com
References:
[1] Dobos N, de Vries FF, Kema IP, Patas K, OPrins M, Nijholt IM, Dierckx RA, Korf J, den Boer JA, Luiten PG, Eisel UL (2012) The role of indoleamine 2,3-dioxygenase in a mouse model of neuroinflammation-induced depression. J Alzheimers Dis, doi: 10.3233/JAD-2011-111097
[2] Anderson G, Ojalla JO (2010) Alzheimer’s and seizures: interleukin-18, indoleamine 2,3-dioxygenase and quinolinic acid. Int J Trytophan Res 3, 169-173.
[3] Nguyen NT, Kimura A, Nakahama T, Chinen I, Masuda K, Nohara K, Fujii-Kuriyama Y, Kishimoto T (2010) Aryl hydrocarbon receptor negatively regulates dendritic cell immunogenicity via a kynurenine-dependent mechanism. Proc Natl Acad Sci U S A 107, 19961-19966.
[4] Opitz CA, Litzenburger UM, Sahm F, Ott M, Tritschler I, Trump S, Schumacher T, Jestaedt L, Schrenk D, Weller M, Jugold M, Guillemin GJ, Miller CL, Lutz C, Radlwimmer B, Lehmann I, von Deimling A, Wick W, Platten M (2011) An endogenous tumour-promoting ligand of the human aryl hydrocarbon receptor. Nature 478, 197-203.
[5] Laugeray A, Launay JM, Callebert J, Surget A, Belzung C, Barone PR (2010) Peripheral and cerebral metabolic abnormalities of the tryptophan- kynurenine pathway in a murine model of major depression. Behav Brain Res 210, 84-91.
[6] Steiner J, Walter M, Gos T, Guillemin GJ, Bernstein HG, Sarnyai Z, Mawrin C, Brisch R, Bielau H, Meyer zu Schwabedissen L, Bogerts B, Myint AM (2011) Severe depression is associated with increased microglial quinolinic acid in subregions of the anterior cingulated gyrus: Evidence for an immune-modulated glutamatergic neurotransmission? J Neuroinflamm 8, 94.
[7] Cermakian N, Lamont EW, Boudreau P, Boivin DB (2011) Circadian clock gene expression in brain regions of Alzheimer’s disease patients and control subjects. J Biol Rhythms 26, 160-170.
[8] Soria V, Martínez-Amorós E, Escaramís G, Valero J, Pérez-Egea R, García C, Gutiérrez-Zotes A, Puigdemont D, Bayés M, Crespo JM, Martorell L, Vilella E, Labad A, Vallejo J, Pérez V, Menchón JM, Estivill X, Gratacòs M, Urretavizcaya M (2010) Differential association of circadian genes with mood disorders: CRY1 and NPAS2 are associated with unipolar major depression and CLOCK and VIP with bipolar disorder. Neuropsychopharmacology 35, 1279-1289.
[9] Qu X, Metz RP, Porter WW, Cassone VM, Earnest DJ (2009) Disruption of period gene expression alters the inductive effects of dioxin on the AhR signaling pathway in the mouse liver. Toxicol Appl Pharmacol 234, 370-377.
[10] Qu X, Metz RP, Porter WW, Neuendorff N, Earnest BJ, Earnest DJ (2010) The clock genes period 1and period 2 mediate diurnal rhythms in dioxin-induced Cyp1A1 expression in the mouse mammary gland and liver. Toxicol Lett 196, 28-32.
[11] Maes M, Galecki P, Verkerk R, Rief W (2011) Somatization, but not depression, is characterized by disorders in the tryptophan catabolite (TRYCAT) pathway, indicating increased indoleamine 2,3-dioxygenase and lowered kynurenine aminotransferase activity. Neuro Endocrinol Lett 32, 264-273.
November 2011
Response to Letter to the Editor from Savitri Hensman
We thank Ms. Hensman for her comments and for her interest in our paper. We note her concerns that we might have overestimated the true costs of dementia in 15 countries of the European Union.
As made clear in our paper, due to the aggregate nature of the data used, the precision of a cost-of-illness study to estimate the burden of a disease across several countries depends on the quality and availability of comparable data across the countries of interest. It is also worth stressing that our study omitted relevant costs including: formal home care provided by social services or paid privately (e.g., home assistance, home help, meals on wheels, etc.) and pharmaceuticals typically consumed by dementia patients such as antipsychotics, anxiolytics, hypnotics, and antidepressants. These costs were not included as there was insufficient information in the majority of countries to make an informed estimate.
In our paper, we clearly highlight the limitations of the study, chief among them the fact that for a number of components, including primary and outpatient care visits, as well as hours of informal care, resource use was derived from published studies following cohorts of diagnosed dementia patients rather than from cases identified using population-based studies.
The numbers of institutionalized patients with dementia was estimated using country-specific data derived from a variety of sources, mainly published studies assessing the prevalence of dementia in those living in long-term care homes on the basis of a clinically oriented assessment interview. In our study, we made the assumption that all dementia patients living in nursing/residential accommodation were institutionalized because of their dementia. Of course, this may not be true for all dementia cases, some of whom will have developed dementia prior to institutionalization. However, as documented in the published literature, dementia is a very strong predictor of institutionalization. In fact, for dementia patients living at home, the main predictors of institutionalization appear to be severity of disease/impairment, age of carer, and carer’s state of health [1-3].
As correctly pointed out by Ms. Hensman, the hours of informal care were derived from studies using samples of diagnosed dementia patients (which excluded non-diagnosed cases). However, it is important to note that not all diagnosed patients have moderate or severe dementia. Furthermore, informal care is also provided to patients with mild dementia. For example, in the study used to estimate hours of informal care in the UK [4], the mean Global Deterioration Scale amongst patients receiving care in the community was 3.72 (i.e., mild cognitive impairment-early dementia).
Regarding the concerns about how the number of outpatient visits was estimated in the UK: The NHS Information Centre’s Hospital Episode Statistics (HES) states that “... primary diagnosis is not a mandated field in the outpatients dataset, therefore coverage within this field is poor” [5]. In 2006-7 there were 51,939,835 outpatient visits in England as recorded by HES. Of these, no primary diagnosis was recorded in 50,666,371 (97.6%) outpatient visits, which were recorded as “Unknown and unspecified causes of morbidity”. For this reason, the number of outpatient consultations for dementia estimated in our study is higher than those recorded in HES.
In summary, despite the limitations that we fully acknowledge in our paper, we believe our study provides a good indication of the economic burden of dementia in 15 European countries.
Ramon Luengo-Fernandez, DPhil; Jose Leal, DPhil; Alastair M. Gray, PhD
Health Economics Research Centre, Department of Public Health, Old Road Campus, University of Oxford, Oxford, UK
References:
[1] Hope T, Keene J, Gedling K, Fairburn CG, Jacoby R (1998) Predictors of institutionalization for people with dementia living at home with a carer. Int J Geriat Psychiatry 13, 682-690.
[2] Agüero-Torres H, von Strauss E, Viitanen M, Winblad B, Fratiglioni L (2001) Institutionalization in the elderly: The role of chronic diseases and dementia. Cross-sectional and longitudinal data from a population-based study. J Clin Epidemiol 54, 795-801.
[3] Hébert R, Dubois MF, Wolfson C, Chambers L, Cohen C (2011) Factors associated with long-term institutionalization of older people with dementia: data from the Canadian Study of Health and Aging. J Gerontol A Biol Sci Med Sci 56, M693-M699.
[4] Schneider J, Hallam A, Murray J, Foley B, Atkin L, Banerjee S, Islam MK, Mann A (2002) Formal and informal care for people with dementia: factors associated with service receipt. Aging Ment Health 6, 255-265.
[5] The NHS Information Centre. Hospital Episode Statistics for England. Outpatient statistics, 2006-07. http://www.hesonline.nhs.uk, Accessed 22 November 2011
Response to article: Luengo-Fernandez R, Leal J, Gray AM (2011) Cost of dementia in the pre-enlargement countries of the European union. J Alzheimers Dis. 27, 187-196.
There has been extensive media coverage recently of the findings of Luengo-Fernandez et al. (2011). Dementia is indeed a costly condition. But, from examining the Supplementary Data (http://www.j-alz.com/issues/27/luengo_supplement.pdf), is it possible that the cost has been over-estimated?
Firstly, was comorbidity and impairment not caused by dementia fully accounted for in estimating social care costs, given that dementia patients often have other conditions requiring care? If, say, a 90-year-old with osteoarthritis, heart failure, and impaired vision would have been able to cope at home with £300 worth of care per week, but because she also had dementia needed to be in a residential home at a cost of £800 per week, would the cost of dementia be calculated as £500 rather than the full £800?
Secondly, with regard to the cost of informal care, when ‘The time spent by relatives and friends providing unpaid care for dementia sufferers was obtained from country-specific studies evaluating the informal care patterns of dementia patients... The average hours of informal care given to each dementia patient was then multiplied by the number of people with dementia living in the community and annualized’, was sufficient account taken of the fact that such studies focus on those receiving care for dementia, while many (especially with mild dementia) do not receive informal or formal care and may not even be diagnosed?
Thirdly, with regard to outpatient visits, did the methodology used result in an excessive figure? In the team’s UK-based study ‘Dementia 2010: the economic burden of dementia and associated research funding in the United Kingdom’ (http://www.dementia2010.org/reports/Dementia2010Full.pdf), it was estimated that in 2006 there were 489,766 outpatient consultations for dementia, but this appears many times greater than the figure in the NHS Information Centre’s Hospital Episode Statistics for outpatient attendances in England (where the majority of the UK population lives) in 2006-7 (Primary diagnosis, 2006-07, Excel file).
Savitri Hensman
London, UK; savihensman@hotmail.com
October 2011
Response to: Zhang et al., A new proposal for randomized start design to investigate disease-modifying therapies for Alzheimer’s disease. Clinical Trials 2011 8: 5-14.
Critical for the increasing prevalence of Alzheimer’s disease and mild cognitive impairment are treatments that modify disease progression rather than providing only symptomatic benefit.
Clinical studies commonly utilize a randomized controlled design, where half, of less than half, of the participants receive a placebo for the study duration. This unfortunately denies treatment to many participants, raising ethical concerns and compromising participation [1]. An alternative is the randomized start design (RSD), where participants are randomized to treatment or placebo for an initial period, after which all participants receive the treatment for the remainder of the study. In addition to increasing participation and compliance, Zhang et al. [2] recently hypothesized that RSD has the unique potential to identify disease modifying (DM) effects versus symptomatic effects since the delayed-start group, once switched to treatment, should display a response equivalent to that of the initial treatment group if the treatment addressed only symptomatic effects. However, should the treatment exert DM, the delayed-start group would not be able to catch up to the initial treatment group due to continued disease progression while on placebo. They present a compelling hypothetical description of these phenomena, and data to support or refute this hypothesis is wanting.
In this regard, during our studies of a nutriceutical formulation (NF; folic acid, vitamin B12, vitamin E, S-adenosyl methionine, N-acetyl cysteine, acetyl-L-carnitine) on cognition and mood in Alzheimer’s disease, we included a RSD study of adults with no known or suspected dementia [3-5]. Since inclusion criteria required absence of any known or suspected cognitive impairment, no relevant DM was encompassed within this study. If the hypotheses of Zhang et al. are correct, the delayed-start group should have attained a level of performance equivalent to that of the initial treatment group. Retrospective examination of our findings as presented herein indicate that this indeed was the case, and therefore provide evidence that supports the use of RSD to detect DM versus symptomatic efficacy.
In our study, 93 participants (both genders, 18-86 years of age) were recruited from community-dwelling individuals. Participants were informed of the trial design during initial presentations, which included randomization to treatment or placebo for the initial 3 months (referred to herein as the “Placebo Phase,” or Period 1, in accord with Zhang et al.), after which code would be revealed and all participants would receive treatment for the remainder of the study (Delayed-start Phase/Period 2). As suggested by Zhang et al., the knowledge that all participants would ultimately receive treatment greatly increased participation. At baseline and subsequent visits, participants completed the Trail-making test (parts A and B), which detects neuromuscular coordination difficulties and the ability to follow simple instructions (part A) and executive function (part B) [6-8]. Scores on A were subtracted from B to isolate effects on executive function. Group performance was statistically compared using an unpaired 1-tailed Student’s t test. In addition, each participant’s baseline score was subtracted from scores at subsequent intervals, and paired t distributions were calculated for each test interval vs. baseline, as well as for the treatment group versus delayed-start group (defined as “delta values” according to Zhang et al.).
The treatment group statistically improved during the placebo phase (i.e., the first 3 months; (p<0.04 versus baseline), while the delayed-start group did not (p<0.24; Fig. 1A); these groups differed statistically at this time (Δ1; p<0.04; Fig. 1A). At the 3-month visit, each participant was informed of prior group assignment. Placebo participants were informed of their switch to treatment (“delayed-start”; Fig. 1A), and after 3 months improved to a level statistically identical to that attained by the treatment group after their first 3 months of treatment (Δ2, p<0.39). The delayed-start group had therefore achieved a level of efficacy equivalent to that of the treatment group within the same respective treatment period.
Additional facets of our study support the RSD. Following the Delayed-start Phase, we withdrew treatment from all participants. After a 3 month “Washout” (Period 3), both groups had declined to levels statistically identical to baseline (p<0.20 and 0.47, respectively) and to each other (Δ3; Fig. 1A). Following resumption of treatment (Resume Phase/Period 4), both groups displayed statistically identical improvement (Δ4; Fig. 1A). These latter findings further indicate that the treatment and delayed-start groups had achieved and maintained statistical identity following the Delayed-start Period.
Zhang et al. point out that if the treatment has no DM effect and only provides symptomatic relief, then the delayed-start group will catch up to the treatment group. By contrast, should the treatment exert DM, the delayed-start group will likely not catch up, and will track differently from the treatment group throughout the remainder of the study. Since we utilized a healthy population, our findings are not intended to address DM but rather are directed entirely to symptomatic effects. The finding that our delayed-start group did indeed catch up to the treatment group, and moreover maintained statistical identity with it through further manipulations (washout and retreatment periods), support the hypothesis of Zhang et al. and, in doing so, provides evidence that RSD has the potential to reveal any DM effect over simple symptomatic effects.
Zhang et al. also address the important concern that code breaking and switching of prior placebo participants to a treatment group, as well as informing the prior treatment group of their status, may induce irregularities in results of an RSD. In this regard, a separate “open-label” cohort (all of which assigned to a treatment group and were aware of it) demonstrated improvement (p<0.04) that was identical to the first 3 months during which the treatment and delayed-start groups received the formulation (Fig. 1B). These findings indicate that the effect of codebreak is minimal and does not invalidate the use of RSD.
This demonstration supports the hypothesis of Zhang et al. that RSD has the capacity to distinguish DM versus symptomatic effects. Coupled with the potential for increased participation, and at least a reduction in the ethical concerns of functionally denying treatment to individuals at risk by maintaining protracted randomization, RSD represents a useful approach for testing novel interventions for AD.
Thomas B. Shea, Ruth Remington
University of Massachusetts • Lowell,
Lowell MA 01854
References
[1] Speigel R., Berres M, Miserez AR, Monsch AU (2011) For debate: Substituting placebo controls in long-term Alzheimer’s prevention trials. Alzheimers Res Ther 3, 9-11.
[2] Zhang RY, Leon AC, Chuang-Stein C, Romano SJ (2011) A new proposal for randomized start design to investigate disease-modifying therapies for Alzheimer’s disease. Clin Trials 8, 5-14.
[3] Chan A, Lepore A, Kotoya E, Zemianek J, Remington R and Shea TB (2010) Efficacy of a vitamin/nutriceutical formulation on cognitive speed and recall in adults with no known or suspected dementia. J Nutr Health Aging 14, 224-230.
[4] Chan A, Paskavitz J, Remington R, Shea TB (2008) Efficacy of a vitamin/nutriceutical formulation for early-stage Alzheimer’s disease: A one-year open-label pilot study with a 16-month extension. Am J Alz Dis Other Dementias 23, 571-585
[5] Remington R, Chan A, Shea TB (2009) Efficacy of a vitamin/nutriceutical formulation for moderate to late-stage Alzheimer’s disease: A placebo-controlled pilot study. Am J Alz Dis Other Dementias 24, 27-33.
[6] Arbuthnott K and Frank J (2000) Trail making test, part B as a measure of executive control: validation using a set-switching paradigm. J Clin Exp Neuropsychol 22, 518-28.
[7] Crowe SF (1998) The differential contribution of mental tracking, cognitive flexibility, visual search, and motor speed to performance on parts A and B of the Trail Making Test. J Clin Psychol 54, 585-91.
[8] Tombaugh TN (2004) Trail Making Test A and B: normative data stratified by age and education. Arch Clin Neuropsychol 19, 203-14.
August 2011
Response to Letter to the Editor from de la Torre
I checked Dr. de la Torre’s papers [1, 2] and found that we do share "advanced aging" in our hypotheses, the well-known greatest risk factor for senile dementia (SD; aka, Alzheimer’s disease). But we also differ significantly in the meaning of "risk factors". While he suggests the importance of morphological and structural changes (deformed microvessels), we emphasize the roles of social, environmental, and lifestyle factors (IQ at young age, social isolation, storytelling, etc.).
In fact, "advanced aging plus risk factors" is street knowledge in the public. It is also shared by many in the medical and clinical community. A search of the keywords "Alzheimer and lifestyle" in PubMed will result in many such papers.
Healthy lifestyle is known as the "key for successful aging" and many people consider SD a "lifestyle disease". Similar views are also found in health books, newspapers, and mass media. So, the model of "advanced aging plus risk factors" is not new, but one going back to common sense, as we emphasized. These issues are further discussed in our recent paper [3].
But the model of advanced aging plus risk factors contrasts sharply with the current dominant hypotheses in the "AD" basic research field, which all assume a single "causal" factor leading to AD. So we together face much more challenging questions:
1. Is it correct to define SD as a "disease" without emphasizing its senile nature?
2. Is there a factor that can contribute to SD more than aging and risk factors in life?
3. What we should logically look for in SD beyond "causal" factors?
4. How to keep the objectivity of science in politically-contentious subjects such as SD?
5. Is SD such a subject?
Ming Chen, Ph.D.
[1] de la Torre JC (1997) Hemodynamic consequences of deformed microvessels in the brain in Alzheimer's disease. Ann N Y Acad Sci 826, 75-91.
[2] de la Torre JC (1999) Critical threshold cerebral hypoperfusion causes Alzheimer's disease? Acta Neuropathol 98, 1-8.
[3] Chen M, Nguyen, HT, Sawmiller DR (2011) What to look for beyond "pathogenic" factor in senile dementia? Functional deficiency of Ca2+ signaling. J Alzheimers Dis, in press.
Response to Article: Chen M, Maleski JJ, Sawmiller DR (2011) Scientific truth or false hope? Understanding Alzheimer's disease from an aging perspective. J Alzheimers Dis 24, 3-10.
I read with interest a recent article by Chen et al. [1] in the Journal of Alzheimer’s Disease (JAD) where the authors review various concepts relating to the possible cause of Alzheimer’s disease (AD). In that paper, Dr. Chen states: “Thus, put together we propose that advanced aging plus risk factors best explain most SD (senile dementia) cases (4)”. That reference “(4)” cites Dr. Chen’s previous paper from Frontiers in Bioscience published in 2001. In that Frontiers article, Dr. Chen writes: “Accordingly, we have further deduced that advanced aging intensified by risk factors most likely underlie late-onset sporadic AD (16, 17)” [2]. The references 16 and 17 provided by Dr. Chen in the Frontiers article refer to two papers previously published in JAD, June 2000, where he briefly affirms: “Accordingly, we proposed a third model, that is, risk factors under the condition of advanced aging can play a primary role in late onset sporadic AD” [3]. In the same paper, Dr. Chen asserts how he arrived at the aging-risk factor concept: “Indeed, it was a surprise to ourselves as well when it first came as an inevitable outcome of our analytic reasoning” [3].
While I am pleased that Dr. Chen finds the concept of aging + risk factors a viable hypothesis to explain the primary cause of sporadic AD, I would like to point out to him that we constructed this concept and published in previous papers to his and in many conference lectures beginning in 1997, when we showed how aging + AD risk factors were associated with the development of AD [4]. This concept was based on extensive experimental and clinical observations from my laboratory as an extension of our vascular hypothesis of AD [5]. The most thorough of those publications discussing AD causality appeared in Acta Neuropathologica in July 1999 [6], (fully a year prior to Dr. Chen’s article in JAD in June 2000), where I reviewed in a lengthy paper the reasoning and the neurodegenerative pathways related to our proposal that advanced aging + AD risk factors are the likely primary trigger leading to cerebral hypoperfusion, neurodegenerative changes and eventual onset of AD [6]. The Acta paper in 1999 was followed by a number of additional papers published in 2000 (also prior to the article by Dr. Chen in JAD in June 2000), extending our thinking and observational evidence on the pathogenesis of AD (see ref [7]). I have not seen any citations to any of our papers on the topic that Dr. Chen claims as his ‘concept’ although I welcome him to the club that considers that AD can be prevented or slowed down by detecting and controlling its major risk factors [8].
J.C. de la Torre, MD, PhD
Professor of Psychology (Adjunct)
University of Texas, Austin
jcdelatorre@comcast.net
References
[1] Chen M, Maleski JJ, Sawmiller DR (2011) Scientific truth or false hope? Understanding Alzheimer's disease from an aging perspective. J Alzheimers Dis 24, 3-10.
[2] Chen M, Fernandez HL (2001) Alzheimer’s disease revisited 25 years later: Is it a “disease” or senile condition? Front Biosci 6, e30-e40.
[3] Chen M, Fernandez HL (2000) How Important are risk factors in Alzheimer's disease? J Alzheimers Dis 2, 119-121.
[4] de la Torre JC (1997) Hemodynamic consequences of deformed microvessels in the brain in Alzheimer's disease. Ann N Y Acad Sci 826, 75-91.
[5] de la Torre JC (2010) The vascular hypothesis of Alzheimer's disease: bench to bedside and beyond. Neurodegener Dis 7, 116-121.
[6] de la Torre JC (1999) Critical threshold cerebral hypoperfusion causes Alzheimer's disease? Acta Neuropathol 98, 1-8.
[7] de la Torre JC (2000) Critically attained threshold of cerebral hypoperfusion: the CATCH hypothesis of Alzheimer's pathogenesis. Neurobiol Aging 21, 331-342.
[8] de la Torre JC (2010) Vascular risk factor detection and control may prevent Alzheimer's disease. Ageing Res Rev 9, 218-225.
May 2011
Response to Letter to the Editor from Masullo et al.
We thank Dr. Bizzarro et al. their observation, which adds important information to our paper.
Their study was not included in the first draft references of our manuscript mainly due to the number of samples used (169 cases and 99 controls). The power of the association and GLM tests on EM estimated haplotypes, calculated according to Shaid et al. showed that we were able to achieve a power of 0.99 only with an almost ten-fold a sample size.
We agree however with the authors that their study strengthens the overall picture of haplotypes and interactions affecting APOE correlation with Alzheimer's and age-related diseases.
Best regards,
Francesco Lescai, PhD, EDBT
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Response to: Lescai et al., An APOE haplotype associated with decreased e4 expression increases the risk of late onset Alzheimer’s disease, J Alzheimers Dis. 2011 Jan 1;24(2):235-45
We have read with interest the paper of Lescai et al.. We were quite surprised by the lack of any reference to a previous study of Bizzarro et al., already reporting these results. In a relative large sample of AD cases from Central and Southern Italy Bizzarro et al. observed a significant association of the -219 (rs405509) polymorphism with AD. Similar, an association of the -219/e4 haplotypes with AD was also reported. Therefore, the study of Lescai et al. in a wide sample of AD patients confirmed the role of the -219 polymorphism as risk factor for AD in Italy and that promoter genotypes and APOE haplotypes might have a complex function as AD-associated genetic risk factors. We feel that the consideration and the evaluation of these results put in the complexity of the discussion of this controversial issue would have been beneficial for the completeness of the published paper and of a major interest for a more analytical information to the readers on the state-of-art on this topic.
Carlo Masullo, MD
Davide Seripa, PhD
Alessandra Bizzarro MD, PhD
Reference
Bizzarro A, Seripa D, Acciarri A, Matera MG, Pilotto A, Tiziano FD, Brahe C, Masullo C. The complex interaction between APOE promoter and AD: an Italian case-control study. Eur J Hum Genet 2009;17:938-945.
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February 2011
Response to Letter to the Editor from Félix Bermejo-Pareja
We thank Dr. Félix Bermejo-Pareja for his astute points about the implementation of the clock drawing test (CDT). We agree that although the CDT is a relatively quick test, it is the scoring that can be problematic. This might contribute to lower than anticipated acceptability. In this study we found that a combination of the Mini-mental State Examination (MMSE) and the CDT was more accurate (largely as a rule-out test) that either test used alone but we acknolwedge this is at a cost of additional time. Most tests have difficulty with case-finding (rule-in) for mild cognitive impairment and Alzheimer's disease versus either mild cognitive impairment or healthy controls and the Mini-clock is no exception. Further research is needed to find the optimal short test for these two uses.
J. Benito-León1,2,3, A.J. Mitchell4, J. Cacho5, R. García-García6, B. Fernández-Calvo7, JL Vicente-Villardón8
1Department of Neurology, University Hospital “12 de Octubre”, Madrid, Spain; 2Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain; 3Faculty of Medicine, Complutense University, Madrid, Spain; 4Department of Liaison Psychiatry (Dr. Mitchell), Leicestershire Partnership Trust and University of Leicester, Leicester, UK; 5Department of Neurology, University Hospital of Salamanca, University of Salamanca, Salamanca, Spain; 6Department of Basic Psychology and Psychobiology, University of Salamanca, Salamanca, Spain; 7Department of Psychology, Federal University of Paraíba, Brazil; 8Department of Statistics, University Hospital of Salamanca, University of Salamanca, Salamanca, Spain
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Could a Combination of the Clock Drawing Test and the Mini-Mental Status Examination Be Used to Screen Dementia in a Neurological Setting? Comments with Data from the NEDICES Survey
The interesting paper recently presented in the Journal of Alzheimer’s Disease [1] suggests, in agreement with one recent report [2], a utilization of the clock drawing test (CDT), in combination with the Mini-Mental Status Examination (MMSE), as a screening method for Alzheimer’s disease (AD) and mild cognitive impairment (MCI) in a neurological setting. . This is a relatively new use of the CDT and MMSE, because both tests are traditionally and preferably employed in these disorders in population- and community-based surveys [3]. It is well known that the use of the CDT in dementia screening has limitations, as it has good screening precision only in moderate and severe dementia cases [4] and in populations without illiterates or subjects with low education [5]. As such, a recent systematic review does not recommend CDT for MCI screening [6], and our experience demonstrated these facts. In the second cross-sectional survey of the Neurological Disorders in Central Spain (NEDICES) cohort (an elderly population-based cohort with low level of education) [7], we screened 3,698 participants in the second cross-sectional survey with an adaptation of the Foltein’s MMSE and a functional scale (FAQ of Pfeffer), and nearly 3,000 subjects also completed a brief neurological test battery. This battery included an executive test (Trail Making Test), several fluency and memory tests, and a verbal intelligence test [8]. A CDT was also included. For evaluating the CDT psychometric properties in this survey, a “convenience” sample (randomly selected but with higher representation of the more aged) of the nearly 3,000 CDTs of the participants was analyzed. Three neurologists and one psychologist blindly evaluated 150 CDTs with the Shulman [9] and Cacho [10] scoring systems. The scoring concordance between the four investigators was not as high as the diagnostic accuracy in the dementia diagnoses employed independently of the scoring system. Currently, the old Spanish population has a cultural level similar to other European countries, but the cultural endowment of the 1997 elderly cohort survey had more than 10% illiterates—complete or functional—and more than 40% who were only able to read and write. With the data of this preliminary study, we decided to not analyze the CDT scores of the participants in the cohort and the work was unpublished. With this experience, however, it is not possible to recommend the use of the CDT in a population with low cultural levels, such as that presented in this paper (the majority of the people were only able to read and write) [5]. It is noteworthy that the completion of the CDT is short (nearly three minutes) but that the interpretation requires time (if it is not done with an elemental scoring system) and experts. Although the authors of this paper certainly meet the expert criteria, most physicians do not have adequate experience.
Furthermore, the data in this study does not demonstrate that the use of the combination of the two tests for MCI and AD screening increases the sensitivity and specificity of this screening in a neurological setting, because these two measures do not increase the screening capacity of these two tests in a statistically significant way.
In summary, this study is interesting and well done, but I think that it does not modify the knowledge that the CDT and MMSE are adequate instruments for dementia screening in population-based and community settings. It is not clear that the combination of both tests increases the efficacy of MCI and AD screening in a neurological setting. As the authors recognize, more studies are needed to demonstrate this efficacy.
Félix Bermejo-Pareja, MD, PhD
Head of Neurology Department. University Hospital “12 de Octubre”. Madrid. Spain
Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Spain
References
[1] Cacho J, Benito-León J, García-García R, Fernández-Calvo B, Vicente-Villardón JL,Mitchell AJ (2010) Does the combination of the MMSE and Clock Drawing Test (Mini-clock) improve the detection of mild Alzheimer's disease and mild cognitive impairment? J Alzheimers Dis 22, 889-96.
[2] Aprahamian I, Martinelli JE, Neri AL, Yassuda MS (2010) The accuracy of the Clock Drawing Test compared to that of standard screening tests for Alzheimer’s disease: results from a study of Brazilian elderly with heterogeneous educational backgrounds. Int Psychogeriatr 22, 64-71
[3] Strauss E, Sherman EMS, Spreen O, eds (2006) A Compendium of Neuropsychological Tests. Third Edit. Oxford University Press. Oxford.
[4] Nishiwaki1 Y, Breeze E, Smeeth L, Bulpitt CJ, Peters R, Fletcher AE (2004) Validity of the Clock-Drawing Test as a screening tool for cognitive impairment in the elderly. Am J Epidemiol 160,797–807
[5] Ainslie NK Murden RA (1993) Effect of education on the clock drawing dementia screen in non demented elderly patients J Amer Geriatr Soc 41, 249-252
[6] Ehreke L, Luppa M,¨KonigHH, Riedel-Heller SG (2010) Is the Clock Drawing Test a screening tool for the diagnosis of mild cognitive impairment? A systematic review. Int Psychogeriatr 22, 56-63.
[7] Morales JM, Bermejo FP, Benito-Leon J, Rivera-Navarro J, Trincado R, Gabriel SR, Vega S; NEDICES Study Group (2004) Methods and demographic findings of the baseline survey of the NEDICES cohort: adoor-to-door survey of neurological disorders in three communities from Central. Spain. Public Health 118, 426-33
[8] Bermejo-Pareja F, Benito-Leon J, Vega S, Medrano MJ, Roman GC; on behalf of the Neurological Disorders in Central Spain (NEDICES) Study Group( 2008) Incidence and subtypes of dementia in three elderly populations of central Spain. J Neurol Sci 264, 63-72
[9] Shulman KI (2000) Clock-drawing: Is it the ideal cognitive screening test? Int J Geriatr Psychiatry 15, 548–561
[10] Cacho J, García-García R, Arcaya J, Vicente JL, Lantada N (1999) A proposal for the application and scoring of the clock drawing test in Alzheimer’s disease (in Spanish). Rev Neurol 28, 648–655.
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December 2010
The article by Walton [1] indicated aluminum is instrumental in causing hyperphosphorylation of tau with subsequent development of neurofibrillary tangle formation. Recently tau has been found to mislocalize to dendritic spines causing early synaptic dysfunction [2]. Aluminum mediated hyperphosphorylation of tau may be a trigger for tau dysfunction and abnormal cellular trafficking with mislocalization to dendrites causing synaptic dysfunction, which probably is an early feature of Alzheimer's disease.
Steven R Brenner, MD
St. Louis VA Medical Center and Department of Neurology and Psychiatry at St. Louis University, St. Louis, MO, USA; Email: SBren20979@aol.com
References:
[1] Walton JR (2010) Evidence for participation of aluminum in neurofibrilllary tangle formation and growth in Alzheimer's disease. J Alzheimers Dis 22, 65-72.
[2] Hoover BR, Reed MN, Su J, Penrod RD, Kotilinek LA, Grant MK, Pitstick R, Carlson GA, Lanier LM, Yuan LL, Ashe KH, Liao D (2010) Tau mislocalizatoin of dendritic spines mediates synaptic dysfunction independently of neurodegeneration. Neuron 68, 1067-1081.
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May 2010
Response to Letter to Editor, Regarding Article: Electromagnetic Field Treatment Protects Against and Reverses Cognitive Impairment in Alzheimer’s Disease Mice by Arendash et al. , J Alzheimers Dis 19:191-210 (2010).
We thank Dr. Kumlin and colleagues for their insightful comments regarding our paper [1]. Inasmuch as we were unaware of their earlier study involving EMF exposure to normal rats [2], we did not include it among the references in our paper and apologize for this oversight. Kumlin et al. [2] did indeed provide initial evidence that long-term EMF exposure (2 hrs/day, 5 days/week, for 5 weeks) can improve cognitive performance in rodents. It is important to note, however, that they provided EMF exposure to very young rats from 3-8 weeks of age. Thus, the authors were actually investigating effects of EMF exposure on immature rats whose brains were still developing—not adult animals. In utilizing the Morris water maze at a single test point, Kumlin et al. found a positive EMF effect only on the first two days of acquisition testing (not on the final two days of testing or overall), so their acquisitional effect was limited to the “rate” of learning. In the retention phase of testing, they found that rats given the higher of two EMF levels utilized (3.0 W/kg SAR) spent more time in the former platform area compared to non-exposed rats (15 sec vs. 10 sec average).
Kumlin and colleagues are incorrect in their assumption that our study utilized a continuous signal without modulation. In fact, our EMF exposure of 918 MHz frequency involved modulation with GMSK signal and was non-continuous with carrier bursts repeated every 4.6 ms, giving a pulse repetition rate of 217 Hz. The electrical field strength varied between 17 and 35 V/m. This resulted in calculated specific absorption rate (SAR) levels that varied between 0.25 W/kg and 1.05 W/kg. SAR was calculated from the below equation, with σ (0.88 s/m) and ρ (1030 kg/m-3) values attained from Nightingale et al. [3]:
SAR = σE2 σ = mean electrical conductivity of mouse brain tissue ρ ρ = mass density of mouse brain E = electrical field strength
In addition, our animals received “near-field” EMF exposure, given that the antenna was one wavelength long and that far-field exposure begins at 2 antenna lengths away from the antenna. Since our antenna length was 12 inches and the distance to mouse cages was 10 inches, mice in our studies received near field EMF exposure, with far-field exposure beginning at 24 inches from the antenna.
We regret that a number of the aforementioned EMF parameters were not mentioned within the methodology of our paper. However, it should now be clear that the EMF parameters used in our mouse whole-body exposure studies closely mimic the EMF exposure provided to the human brain by a typical cell phone, which is why our study is directly relevant to human cell phone use.
In reference to Kumlin et al. observing cognitive benefits after 5 weeks of EMF exposure, while we reported cognitive benefits in our study beginning at 5 months into EMF exposure, this difference in onset of cognitive benefit is most likely due to: 1) their use of immature, adolescent rats wherein EMF effects could be more easily attained in comparison to our use of adult mice, and/or 2) the much higher (above cell phone level) SAR level employed in their study. Regarding the later, there really was no effect of their EMF exposure on Morris maze “overall” or “final” acquisition, with only a modest enhancement of retention in the probe trial observed at a very high SAR level. By contrast, our paper in “adult” mice involved both normal and Alzheimer’s mice (approximately 100 mice total) given cell phone-level SAR exposure in both protection- and treatment-based studies, tested at multiple time points, and in multiple cognitive tasks. Moreover, several of our cognitive tasks (i.e., the radial arm water maze and cognitive interference task) are far more challenging than the Morris water maze used by Kumlin et al. and involve working/short-term memory rather than the spatial long-term learning/memory evaluated in the Morris maze.
Regarding the comment that there was a surprisingly large increase in body temperature with long-term EMF exposure in mice of our study, we wish to make three points. First, the increase in body/brain temperature (of approximately 1ºC) was consistently observed only in the Alzheimer’s mice and only with long-term (not acute) EMF exposure—normal mice did not consistently show an increase in temperature during EMF exposure. Second, our mice were given longer and more consistent EMF exposure (daily for 8-9 months) than any prior study involving cell phone parameters. Third, Alzheimer’s transgenic mice and their brain Aβ burdens had never before been a subject of EMF studies. Thus, Kumlin et al. are questioning a result that had no prior precedent of what to expect from the literature. What is clear is that the 1ºC increase in body/brain temperature during our EMF exposure to AD mice is a minimal increase that is well below the 41ºC level that begins to result in mammalian brain damage. Moreover, fluctuations of 2ºC or higher in mammalian brains occur regularly, depending on behavioral and metabolic state. Thus, our observed 1ºC elevation in temperature during EMF exposure to AD mice would appear to be safe and cognitively beneficial. It is noteworthy that this increase in body/brain temperature of AD mice during EMF exposure periods occurred at SAR levels (0.25 – 1.05 W/kg) that are well within, and indeed typical of, SAR levels during cell phone use.
Kumlin et al. are mistaken in suggesting that the temperature data from our long-term and acute studies are not directly comparable since only the acute studies involved brain temperature measurement. In fact, the group comparisons for both types of studies are comparable in view of the high correlation (r=0.98) between body temperature and brain temperature that we also presented. Thus, an increase in body temperature would certainly mean an identical increase in brain temperature for the long-term studies, despite our not having measured brain temperature in the long-term studies. Kumlin et al. also believe that, because our temperature recording occurred during EMF exposure, that the temperature probes may have been subjected to interference from the EMF signal. If this was an issue, however, all measurements would be expected to have the same interference, not just those from AD mice and not just those from long-term studies.
Kumlin et al. further suggest that the EMF dose used in our studies is not known. However, as we have now provided fuller details of our EMF exposure methodology, the EMF dose utilized in our studies is now abundantly clear. It should also be evident that the EMF parameters utilized were indeed very similar to those emitted by typical cell phones during their use. We agree with Kumlin et al. that it is important to investigate the dose-response relation in future EMF studies. In that context, our ongoing studies are investigating the best set of EMF parameters for achieving cognitive benefits in the shortest amount of time (if previous cognitive impairment is present), and without incurring any undesirable side-effects.
Finally, we would like to indicate our excitement over the inception of a new field of cognitive neuroscience by recent studies such as ours and Kumlin et al.—namely, Cognitive Benefits of EMF Exposure. Explored in a conscientious manner, with well-designed studies and appropriate behavioral endpoints, this new emerging field could provide a surprising array of benefits against diseases of brain aging.
Gary W. Arendash
Dept. of Cell Biology, Microbiology, and Molecular Biology
University of South Florida
Tampa, FL
Chuanhai Cao
USF/Byrd Alzheimer’s Disease Research Institute
University of South Florida
Tampa, FL
[1] Arendash GW, Sanchez-Ramos J, Mori T, Mamcarz M, Lin X, Runfeldt M, Wang L, Zhang G, Sava V, Tan J, Cao C. Electromagnetic field treatment protects against and reverses cognitive impairment in Alzheimer's disease mice. J Alzheimers Dis. 2010 Jan;19(1):191-210.
[2] Kumlin T, Iivonen H, Miettinen P, Juvonen A, van Groen T, Puranen L, Pitkäaho R, Juutilainen J, Tanila H. Mobile phone radiation and the developing brain: behavioral and morphological effects in juvenile rats. Radiat Res. 2007 Oct;168(4):471-9.
[3] Nightingale NR, Goodridge VD, Sheppard RJ, Christie JL. The dielectric properties of the cerebellum, cerebrum and brain stem of mouse brain at radiowave and microwave frequencies. Phys Med Biol. 1983 Aug;28(8):897-903.
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Response to article: Perucho J, Rubio I, Casarejos MJ, Gomez A, Rodriguez-Navarro JA, Solano RM, de Yebenes JG, Mena MA (2010) Anesthesia with isoflurane increases amyloid pathology in mice models of Alzheimer’s disease. J Alzheimers Dis 19, 1245-1259.
We note that Perucho et al. [1] cite (reference number 28) a 2007 publication by Pravat K Mandal [2], and we wish to point out to the authors and your readers that the Biochemistry paper in question was retracted later that same year [3], as was another article by Mandal [4], because “the anesthetic concentration of our paper[s] was misrepresented”. Those papers should therefore not be cited as evidence.
We also note in passing that the reference to Mandal’s retracted paper was incomplete (missing two authors [2]) and another citation of the work of Mandal and Fodale (reference 7 in Perucho et al) is also misreferenced. The citation to the latter should be 2009, not 2006, and the title of both the article and journal are incorrect [5].
Dr John Loadsman, MB, BS, PhD, FANZCA
Conjoint Senior Lecturer and Staff Specialist
Department of Anaesthetics
University of Sydney and Royal Prince Alfred Hospital
Camperdown 2050
Australia
Dr Francois Stapelberg, MBChB, FANZCA
Specialist Anaesthetist
Department of Anaesthesia
Senior Clinical Lecturer
University of Auckland and Middlemore Hospital
Auckland 1640
New Zealand
References:
[1] Perucho J, Rubio I, Casarejos MJ, Gomez A, Rodriguez-Navarro JA, Solano RM, de Yebenes JG, Mena MA (2010) Anesthesia with isoflurane increases amyloid pathology in mice models of Alzheimer’s disease. J Alzheimers Dis 19, 1247-1259.
[2] Mandal PK, Williams JP, Mandal R (2007) Molecular understanding of Abeta peptide interaction with isoflurane, propofol, and thiopental: NMR spectroscopic study. Biochemistry 46, 762-771.
[3] Mandal PK (2007) Molecular understanding of Abeta peptide interaction with isoflurane, propofol, and thiopental: NMR spectroscopic study. [Retraction of Mandal PK, Williams JP, Mandal R. Biochemistry. 2007 Jan 23;46(3):762-71; PMID: 17223697] Biochemistry 46, 12887.
[4] Mandal PK. Pettegrew JW (2008) Alzheimer's disease: halothane induces Abeta peptide to oligomeric form - solution NMR studies. [Retraction of Mandal PK, Pettegrew JW, McKeag DW, Mandal R. Neurochem Res. 2006 Jul;31(7):883-90; PMID: 16807784] Neurochem Res 33, 220.
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April 2010
Response to article: Cholinesterase activity and mRNA level of nicotinic acetylcholine receptors (α4 and β2 Subunits) in blood of elderly Chinese diagnosed as Alzheimer’s disease by Zhang et al., J Alzheimers Dis 19:849-858 (2010).
In a recent issue of Journal of Alzheimer’s Disease, Zhang and colleagues presented interesting data concerning the cholinergic deficit in Alzheimer’s disease (AD) [1]. These results demonstrated decreases in the activity of acetylcholinesterase (AChE) and reduced mRNA levels of α4 and β2 nicotinic acetylcholine receptor (nAChR) subunits in peripheral blood of patients with AD in an elderly Chinese population. Although accumulating evidence indicates that changes in the AD brain may be reflected by alterations in the peripheral blood cells of AD patients, there are not, as yet, universally accepted biological tests for an unequivocal diagnoses of the disease. As such, an important aspect of this study was that these alterations might be used as supplementary markers for the diagnosis of AD. However, there are several points that merit discussion.
First, as stated in the article, the mean score of MMSE tests for AD patients was 10.25±5.77. Therefore, we understand that all of patients were moderate and severe stages. The natural history of AD has a broad spectrum considered as a presymptomatic stage during which a number of pathological events take place over many years, an early symptomatic or prodromal stage [amnestic-mild cognitive impairment (aMCI)] with cognitive and, at times, neuropsychiatric manifestations, and symptomatic mild, moderate, and severe stages. It should be noted that decline is faster in the moderate and severe stage related to the natural progression of AD. While hopes for reversibility of pathological changes target the early stages of AD (aMCI and mild stage) for disease modification, unfortunately, diagnosis of aMCI and mild stage AD is problematic in general practice [2].
Second, anticholinergic drug use increases with advanced age because of frequently emerging disorders such as chronic obstructive lung disease, overactive bladder, and irritable bowel syndrome. Unfortunately, there was no information about anticholinergic drugs taken from patients or control subjects in the published study. This is important due to the fact that it is known that acetylcholine effect is blocked by these drugs [3-5], and we think that increased acetylcoline may cause changes in AChE activity.
In conclusion, we suggestion that future studies assess aMCI and mild stage AD where the early initiation of cholinesterase inhibitors therapy may defer the progression of disease and may prolong survival time. For this reason, all physicians need a marker for the early stages of AD. Also, as indicated, the confounding effects of any anticholinergic drug is important to consider. The aspects would certainly provide insights into the future identification of candidates with diagnostic biomarkers in peripheral blood.
Mehmet Ilkin Naharci, MD
Gulhane School of Medicine, Department of Internal Medicine, Division of Geriatrics, Ankara, Turkey; Tel: +90-312-304 31 22, Fax: +90-312-304 31 03, Email: inaharci@gata.edu.tr
Huseyin Doruk, MD
Gulhane School of Medicine, Department of Internal Medicine, Division of Geriatrics, Ankara, Turkey
Ergun Bozoglu, MD
Gulhane School of Medicine, Department of Internal Medicine, Division of Geriatrics, Ankara, Turkey
References:
[1] Zhang LJ, Xiao Y, Qi XL, Shan KR, Pei JJ, Kuang SX, Liu F, Guan ZZ (2010) Cholinesterase activity and mRNA level of nicotinic acetylcholine receptors (α4 and β2 Subunits) in blood of elderly Chinese diagnosed as Alzheimer’s disease. J Alzheimer’s Dis 19, 849-858.
[2] Spar JE, La Rue A (2006) Dementia and Alzheimer disease. In Clinical Manual of Geriatric Psychiatry, Washington DC, eds. American Psychiatric Publishing, London, pp. 173-229.
[3] Buhling F, Lieder N, Ulrike C, Kühlmann UC, Waldburg N, Welte T (2007) Tiotropium suppresses acetylcholine-induced release of chemotactic mediators in vitro. Respir Med 101, 2386–2394.
[4] Matsui T, Kimura I, Kimura M (1990) Increase in the activities of plasma pseudocholinesterase dependent on the blood glucose level and its relation to the hypersensitivity to acetylcholine in striated muscles of KK-CAy mice with diabetes. Jpn J Pharmacol 54, 97-103.
[5] Pieper MP, Chaudhary NI, Park JE (2007) Acetylcholine-induced proliferation of fibroblasts and myofibroblasts in vitro is inhibited by tiotropium bromide. Life Sci 80, 2270-2773.
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March 2010
Response to Article: Alzheimer’s Disease Research: Scientific Productivity and Impact of the Top 100 Investigators in the Field by: Aaron A. Sorensen, J Alzh Dis v.16, 451-465.
To the Editors
Like many with an interest in the field of Alzheimer’s disease I was intrigued to read the recent paper in JAD which purported to report the ‘scientific productivity and impact of the top 100 investigators in the field’ [1]. As an outsider to the study of ‘scientometrics’ it appeared a thorough piece of work though there were few indications as to its actual aims. If ‘productivity and impact’ are purely numerical indices then the study has succeeded in informing us whom has published the largest number of papers on Alzheimer’s disease and how often this body of papers has been cited. Perhaps of equal importance to the recognition of the ‘top’ 100 investigators in Alzheimer’s disease the study has also informed as to the areas of Alzheimer’s disease research which have received the largest research effort.
While I am sure that these data will now be used in myriad ways to support the significance of both individuals and research areas they should not be allowed to distract us from the stark realities of Alzheimer’s disease itself. By which I mean that in spite of the ‘scientific productivity and impact’ of these ‘top’ 100 invesitigators; (i) we still do not know the cause of Alzheimer’s disease, (ii) there is no cure for Alzheimer’s disease, (iii) there are no truly effective treatments for Alzheimer’s disease. While we can all argue around the ‘edges’ of each of these statements we all know that they are basically correct and that we remain some distance away from offering individuals diagnosed with Alzheimer’s disease the kind of hope that does exist for other common fatal diseases such as cancer and heart disease.
I have a vain hope that we might look at this scientometric exercise and, in particular, what it tells us about the scientific areas where the vast majority of this research has been carried out and conclude that, for a limited amount of research funding, we are putting too much effort into these areas. The very heavy emphasis upon beta amyloid and tau as prime research targets in elucidating the cause of Alzheimer’s disease, while having revealed much of great interest and fascination, has not been successful in combatting or treating the disease. I do not advocate stopping these lines of enquiry only that they should not be followed at the expense of other possibilities. The paper by Sorensen demonstrates that not only is AD research completely dominated by these subjects but that there is little chance that this will change while the most influential researchers in the field continue to support such studies. If you are one of the ‘top’100 identified in Sorensen’s paper then your ‘productivity and impact’ to-date in Alzheimer’s disease is, upon application of Occam’s razor, purely academic. You should be congratulated on this but you must now use your influence to look beyond the research of the past 40 years to the research of the future 40 years such that in time, and hopefully soon, we will be able to offer hope to the burgeoning numbers of individuals diagnosed with AD.
Christopher Exley PhD
Reader in Bioinorganic Chemistry
The Birchall Centre, Lennard-Jones Laboratories,
Keele University, Staffordshire, ST5 5BG, UK
Tel: 44 1782 734080; Email: c.exley@chem.keele.ac.uk
http://www.keele.ac.uk/depts/ch/groups/aluminium/index.html
Honorary Professor, UHI Millennium Institute
References:
[1] Sorensen AA (2009) Alzheimer’s disease research: Scientific productivity and impact of the top 100 investigators in the field. J Alzh Dis 16, 451-465.
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Response to Article: Electromagnetic Field Treatment Protects Against and Reverses Cognitive Impairment in Alzheimer’s Disease Mice by Arendash et al. , J Alzheimers Dis 19:191-210 (2010).
A very interesting article by Arendash et al. (1) was published in the January 2010 issue of Journal of Alzheimer’s Disease. The results suggested that exposure to radiofrequency (RF) radiation similar to that emitted by mobile phones may provide cognitive benefits both in normal mice and in a transgenic mouse model of Alzheimer’s disease (AD).
In the Introduction, the authors state “To date, no controlled long-term studies of high frequency /cell phone EMF effects on cognitive function have been done in humans, mice, or animal models for AD.” Although the sentence is very true as it is (because rats are not specifically mentioned), another sentence in the Abstract – “this report presents the first evidence that long-term EMF exposure directly associated with cell phone use…provides cognitive benefits” – is certainly not true. In a paper published two years earlier (2), we reported improved learning and memory in water maze tests in young male Wistar rats exposed to a mobile phone RF signal for 5 weeks.
The electromagnetic field exposures in the two studies were similar though not identical: Arendash et al. exposed the animals to a 918 MHz electromagnetic field for 2 h/day at a (reported) exposure level of 0.25 W/kg for 2 h/day, whereas we used a 900 MHz field for 2 h/day at 0.3 or 3 W/kg. However, there are also some differences. We used a pulse-modulated signal similar to that emitted by GSM mobile phones, whereas Arendash et al. probably used a continuous signal (no modulation is reported in the paper). The most important difference in the results is that we found improved learning and memory already after 5 weeks of exposure, while Arendash et al. reported no beneficial effects before 5 months of exposure. It remains to be investigated whether this difference is related to differences in exposure level; a shorter exposure time might be sufficient to cause effects at higher exposure level. We found some evidence of a dose-response relationship - improved task acquisition was found in both exposed groups, but improved memory retention was observed only in the higher exposure group. Of course, differences in results may also be related to the fact that animal models and testing methods were not identical in the two studies.
A major weakness in the article of Arendash et al. is insufficient characterization of the electromagnetic field exposure system and dosimetry. The description of the exposure system is very brief and, most importantly, there is no information on how the specific absorption rate (SAR, the “dose” of RF radiation) was determined. The physics of RF electromagnetic fields is very complex, and exposing animals to a well-defined “dose” is much more difficult than giving a dose of a chemical. Adequate reporting of the dosimetry is therefore essential in any study reporting biological effects of RF radiation. The complexity of the issue is well illustrated in the paper (3) that reports the technical details and dosimetry of the exposure system used in our rat study. Arendash et al. reported surprisingly large increase of body temperature (over 1 °C) in the exposed animals during 1-hour exposure periods. The reported SAR level of 0.25 W/kg is so low that it should not result in measurable increase of body temperature, which raises doubts that the true SAR may have been higher than was reported. The authors’ interpretation was that the temperature increase (seen during 1-h exposure of animals that had been exposed for 8 months) was not a result of direct heating, and they presented data showing that single acute exposures did not increase brain temperature. However, the temperature data from the acute and long-term studies are not directly comparable, as the measurement methods were different (rectal vs. temporal muscle probe). That the temperature measurements (both with the rectal probe and the temporal muscle probe) were performed during electromagnetic field exposure introduces additional problems for the interpretation of the temperature data: the electromagnetic field may have coupled directly into the probes (which can act as antennas) and the resulting interference may have biased the readings up or down.
Inadequate dosimetry does not totally invalidate the results of Arendash et al. The “medicine” is promising although the dose used in the trial is not known. Given that positive effects on cognitive function are supported by two independent experimental studies and recent epidemiological findings (4), it is easy to concur with the conclusions of Arendash et al. that these surprising findings justify RF electromagnetic field exposure “as a non-invasive, non-pharmacologic approach worthy of vigorous investigation”. Like in the case of pharmacological agents, it is important to investigate the dose-response relationship, so any further experimental studies should include proper reporting of dosimetry and preferably more than one exposure level.
Timo Kumlin and Jukka Juutilainen
University of Eastern Finland
Department of Environmental Science
P.O.Box 1627, FI-70211 Kuopio
Finland
Heikki Tanila
University of Eastern Finland
A.I.Virtanen Institute for Molecular Sciences
Kuopio, Finland
Lauri Puranen
STUK- Radiation and Nuclear Safety Authority
Helsinki, Finland
References:
1. Arendash GW, Sanchez-Ramos J, Mori T, Mamcarz M, Lin X, Runfeldt M, Wang L, Zhang G, Sava V, Tan J, Cao C. Electromagnetic field treatment protects against and reverses cognitive impairment in Alzheimer's disease mice. J Alzheimers Dis. 2010 Jan;19(1):191-210.
2. Kumlin T, Iivonen H, Miettinen P, Juvonen A, van Groen T, Puranen L, Pitkäaho R, Juutilainen J, Tanila H. Mobile phone radiation and the developing brain: behavioral and morphological effects in juvenile rats. Radiat Res. 2007 Oct;168(4):471-9
3. Puranen L, Toivo T, Toivonen T, Pitkäaho R, Turunen A, Sihvonen AP, Jokela K, Heikkinen P, Kumlin T, Juutilainen J. Space efficient system for whole-body exposure of unrestrained rats to 900 MHz electromagnetic fields. Bioelectromagnetics. 2009 Feb;30(2):120-8.
4. Schüz J, Waldemar G, Olsen JH, Johansen C. Risks for central nervous system diseases among mobile phone subscribers: a Danish retrospective cohort study. PLoS One. 2009;4(2):e4389.
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an IOS Press publication
