Recent comments

  • Reply to: Comment on Aluminum and Amyloid-in Familial Alzheimer’s Disease   1 week 4 days ago

    In January 2020 immediately following the publication of our ‘landmark’ (as described by George Perry, Editor-in-Chief of JAD) paper on Al in brain tissue in FAD, two anonymous comments were posted on website PubPeer. This website describes itself as ‘the online journal club’. Really? An online journal club that supports anonymous comments about peer-reviewed published science. PubPeer is no more than a publishing platform for trolls. A recent review of the content of this site found that almost 90% of submitted comments were anonymous. The owners of the site stating that anonymity protects graduate students wishing to comment on published science. Really? Or perhaps it is because no one used the site before they introduced anonymity. Either way, why would any repoutable scientist use this platform for science?

    The anonymous comments were made by someone calling themselves Hoya camphorifolia, a plant. An interesting choice of disguise for a troll, charged with planting seeds of doubt into any published science that does not follow the industry narrative.

    We now learn that the anonymous plant Hoya camphorifolia is Abraham Al-Ahmad a ‘scientist’ working at Texas Tech University. One does wonder how this person has time to do any science bearing in mind that he has made over 2000 comments on PubPeer over the past few years. He is clearly a talented polymath as he has no reservations about commenting upon almost any subject. He has used his extensive knowledge and understanding to follow up his anonymous comments on PubPeer to submit a Letter to the Editor on our paper (and indeed all of our research on aluminium in human health).

    I have no issue with any legitimate commentary on our research. In fact I welcome all informed discussion of our published research.

    I do have an issue with how this Letter to the Editor has come about.

    I would like George Perry to explain why in February of this year, four years after the anonymous comments were left on PubPeer, he invited an anonymous plant to write a Letter to the Editor about their issues with our paper. Is this normal practice for a journal editor? If so, why now, why not when the anonymous comments were made in January 2020.

    I am then further perplexed by what exactly constitutes a Letter to the Editor? In my forty years or so in science I have always understood that Letters to the Editor about a paper published in their journal would in the first instance be peer-reviewed, commonly by the original reviewers of the published paper. If upon peer review it is decided that the Letter is worthy of publication then the authors of the paper in question are afforded an opportunity to reply to the Letter. I would like George Perry to explain why this procedure was not followed for this Letter about our paper.

    I have supported JAD with my very best research almost since the first volume. I have enormous respect for George Perry, an exceptional scientist and an editor with integrity. The latter being something of a rarity these days. So, why did George Perry follow this course of action? Why did he decide to allow a known troll to publish a non-peer-reviewed unfounded comment about a paper that he himself described as a ‘landmark’ paper. George Perry has always, at least up until now, stood up for fairness and integrity in science. He has always put good science first. What or who changed this?

    I have never replied to any anonymous, non-peer-reviewed comments about our research. I am not about to start doing so now. For an editor that I have always held in very high esteem to ask me to do so now is to say the very least disappointing but even more it is worrying that someone with intergrity might be so easily corrupted, probably by the power of publishers and those that control them. The aluminium industry failed in preventing science opening up their Pandora's box. We now only have to look inside to know the damage that aluminium continues to wreak on humanity.

  • Reply to: Comment on Aluminum and Amyloid-in Familial Alzheimer’s Disease   2 weeks 2 days ago

    I cannot believe that you have published this complete scientific nonsense without it being peer reviewed by the original reviewers of the paper. Surely this is the usual practice for any Letter to the Editor? If following such peer review the conclusion was that the points raised had some legitimacy then we would have gladly answered such comments. You did not afford us this opportunity and for someone who has published with JAD almost from its first volume this is extremely disappointing.

    I appreciate the comment by Dr John Savory and I thank him for his time and support. However, he is not to know the nature of the individual submitting these comments. He is also not to know that this individual has been writing his scientific nonsense on behalf of the aluminium industry on every open platform on the internet. He is a troll, no more or less. I am appalled that JAD has not recognised this. He will now use your letter to support his views throughout the internet. You are allowing him to spread his misinformation through a respected source, JAD.

    I also question the suggestion by the author of this internet nonsense that you, JAD, actually asked for comments on this paper. Is this true?

  • Reply to: Comment on Unleashing the Power of Bayesian Re-Analysis   2 weeks 4 days ago

    I would like to thank Dr. Liloia and colleagues for their clarification. Contrary to their argument, however, I do not see how the decision to use a one-tailed rather than a two-tailed test of superiority would affect the estimate of the standard error (SE) and the resulting value of the T statistic. Of course, it affects the p-value or the Bayes factor. Dr. Liloia and colleagues cite van Ravenzwaaij et al. [1]. When one follows these authors [1], the SE estimate is based on the confidence interval (CI) as follows:
    SE = (0.5*width of the two-sided CI)/ t(df, p < 0.025).
    Applying this formula to the data of the Lecanemab trial [2] data yields:
    SE = 0.5*|-0.67- -0.23|/ t(df, p < 0.025) = 0.22/1.96 = 0.11.
    This gives a T statistic of -0.45/0.11= -4.  

    The SE estimate of a measurement is not affected by the decision to use a one-tailed or two-tailed superiority test. For the frequentist analysis, the one-tailed vs. two-tailed decision affects the selection of the critical t-value. For the Bayesian analysis in the JASP software (version 0.18.3), the T-statistic of -4 yields a Bayes factor for the two-tailed difference of Lecanemab vs. placebo (i.e., undirected effect) of 145.3. For the one-tailed superiority test under the assumption that Lecanemab is superior to placebo (directional effect in favor of Lecanemab), the Bayes factor is 286.5, and for the one-tailed superiority test under the assumption that placebo is superior to Lecanemab (directional effect in favor of placebo), the Bayes factor is 0.01. Using the formula of van Ravenzwaaij et al. [1], we thus obtain a Bayesian estimate that is consistent with the frequentist result and indicates extreme evidence in favor of a superior effect of the active compound and extreme evidence against a superior effect of placebo. The estimate of both the frequentist p-value and the Bayes factor are affected by the decision to use a one-tailed or two-tailed test, but the estimate of the SE is not.

    Conflict of Interest:
    S.T. has served on advisory boards for Lilly, Eisai, and Biogen and is a member of the Independent Data Safety and Monitoring Board for the ENVISION trial (Biogen).

    References:
    [1]    van Ravenzwaaij D, Monden R, Tendeiro JN, Ioannidis JPA (2019) Bayes factors for superiority, non-inferiority, and equivalence designs. BMC Med Res Methodol 19, 71.
    [2]    van Dyck CH, Swanson CJ, Aisen P, Bateman RJ, Chen C, Gee M, Kanekiyo M, Li D, Reyderman L, Cohen S, Froelich L, Katayama S, Sabbagh M, Vellas B, Watson D, Dhadda S, Irizarry M, Kramer LD, Iwatsubo T (2023) Lecanemab in early Alzheimer's disease. N Engl J Med 388, 9-21.

  • Reply to: Comment on Aluminum and Amyloid-in Familial Alzheimer’s Disease   2 weeks 6 days ago

    Much of the concern expressed by Al-Ahman revolves around the use of tissue specimens for assessing aluminum accumulation and the imprecision of the analytical measurements. Tissue has always been recognized as an appropriate specimen for assessing body burden of metals but has the disadvantage of being heterogeneous and, hence, two samples located close to each other often give widely divergent results. Due to this reason, biological fluids, rather than tissue, are most commonly used to assess body burden of metals but unfortunately this often does not reflect body burden. A good example is zinc where plasma or urine analysis can provide accurate and precise measurements that have little bearing on assessing body burden. Tissue analysis gives much better results but side by side samples often to not agree. Also of course obtaining a tissue specimen is unpleasant for the patient and phlebotomy or urine collection is much simpler. Lymphocyte analysis has been proposed as a compromise and has shown much promise, but I do not think it is widely used at the present time especially since zinc deficiency is not a major health issue. When aluminum was first shown to be a major health issue in hemodialysis patients it was important to standardize the analytical assessment of body burden of aluminum. Serum measurements had their limitations, and tissue and bone analysis was proposed and used in a few dialysis centers. Fortunately, serum or plasma did provide a reasonable means of assessing body burden and are now the specimen of choice. Lymphocytes were also considered but did help much and I do not think offered any advantages over serum or plasma measurements. Obviously, the only specimen which can be used to assess aluminum accumulation in the central nervous system is brain tissue, which requires extensive processing prior to the final measurement. It appears that Exley recognized this, and he and his coworkers did the best they could at trying to show that aluminum accumulation does occur in Alzheimer's disease affected patients. The more brain tissue that is available then the precision of the measurement would improve, but it appears that the amount of brain tissue available to the Exley group was limited. Despite the limitations of the use of brain tissue and its heterogeneity, it appears to me that valuable information was forthcoming from the study and deserved to be published. Perhaps, however, Dr. Exley could have been less dogmatic in expressing his conclusions that aluminum does cause Alzheimer's disease. Al-Ahman expresses some concern about the precision of the electrothermal atomic absorption technique. This is a tried-and-true technology that was developed in the 1960s and first applied to the analysis of biological specimens in 1973. It is both an accurate and precise technique and Exley and his group have had extensive experience with the analytical system. There are newer techniques but are not without their drawbacks. The use of mass spectrometry for the final measurement also has problems with polyatomic interferences which require high resolution mass spectrometry to obtain the best data. Yes perhaps Dr. Exley was somewhat dogmatic about stating definitively that aluminum and Alzheimer’s disease are intertwined, but it could be pointed out that those neuroscientists who support the Aβ hypothesis are equally dogmatic about their confidence that Aβ accumulation is central to the development of Alzheimer's disease. How many thousands of times has this been stated over the past 40 plus years. Countless millions of dollars have been expended on drug development and treatments that still are of little value. Since aluminum is so highly abundant on Planet Earth, we will probably never know if this element is the primary cause of the disease or perhaps if the biochemical and neuropathological abnormalities observed in the disease just happen to possess affinity for aluminum. This would not be surprising since the toxic aluminum species Al3+ is highly reactive and has a high affinity for phosphorylated proteins. One feature of the aluminum hypothesis that provides support for aluminum playing an important role in the development of Alzheimer’s and related disorder is that most of the biochemical and neuropathological changes seen in Alzheimer’s disease can be reproduced in experimental animals. Very few neuroscientists understand the complex chemistry of aluminum, yet this is central to designing meaningful experiments. Additionally, the selection of appropriate animal model systems is extremely important, and the use of rabbits is an obvious choice since they more closely resemble primates than rodents [1]. With this animal model system and using aluminum maltolate as the preferred aluminum compound remarkable similarities between Alzheimer's disease patients and the changes seen in rabbits, are observed. This is an acute exposure to the animals and requires the intracerebral administration of aluminum maltolate. Comparison of the changes in Alzheimer’s disease and the acute exposure in rabbits is summarized in the following Table. There is a remarkable similarity with the exception that paired helical filaments in the animal model are not observed, although there are intraneuronal neurofilamentous aggregates that are positive for hyperphosphorylated tau. It could be argued that once these intraneuronal neurofilamentous aggregates are in place then a structural rearrangement could occur with time—perhaps months or years.

    Imagine what interesting studies could have been forthcoming if a fraction of the funding for Aβ research could have been redirected. Yet the only argument against the aluminum hypothesis is that “Everyone knows that aluminum does not cause Alzheimer’s disease”. This is widely stated by the vast majority of physicians/neuroscientists and, of course those working for the best interests of the aluminum industry. This is despite the data shown above and the fact that aluminum is the most abundant metal in the earth’s crust and the third most abundant element. Fortunately, aluminum is locked in complex inorganic and organic species making it relatively innocuous except perhaps in certain individuals and also as a result of the aging process. Good science would undoubtedly have contributed a great deal to such a field of research.

    On a personal note, in my old age I see memory loss in members of my own family and I greatly resent the anti-aluminum faction of our society led by the aluminum industry who have spearheaded the charge to stifle any research that might affect the image of aluminum. Dr. Exley has made many excellent contributions to carry the banner of the aluminum hypotheses, not least of which are the international conferences that he has organized in memory of his mentor, Dr. Derek Birchall.
    I hope what I have written is helpful to you in assessing what to do about the PubPeer submission. I had not heard of PubPeer until I received your email, but it sounds like an interesting approach to stimulating discussion especially concerning controversial topic. Some of my comments are just a means of letting off steam but so much could have been accomplished to understand what could be an important line of research to help those with this dreadful neurodegenerative disease. I have written most of the above from memory. Perhaps in my old age I have been spared the consequences of brain aluminum accumulation—I am 88 years old which puts me in a vulnerable age group for Alzheimer's disease.

    John Savory

    Reference
    [1] Graur D, Duret L, Gouy M (1996) Phylogenetic position of the order Lagomorpha (rabbits, hares and allies). Nature 379, 333–335.

  • Reply to: Comment on Unleashing the Power of Bayesian Re-Analysis   2 weeks 6 days ago

    We thank Prof. Stefan Teipel, author of the Letter to the Editor, for his comment on our recently published Research Article [1], as well as for appreciating our previous Bayesian meta-analysis of the Aducanumab Phase 3 trials [2]. We also express our gratitude to the Editor-in-Chief for granting us the opportunity to clarify the point raised.

    The criticism of our work pertains to the calculation of the effect size estimate, which yields results contradicting those of the frequentist analysis presented in the study by van Dyck et al. [3]. Specifically, the author contends that we derived an inflated estimate of standard error (i.e., 0.22 instead of 0.11), resulting in half of the effect size that would have been obtained based on the formulas by Higgins et al. [4].

    While we acknowledge the accuracy of the author's implementation of the standard error calculation for the specific scenario targeting the determination of a two-tailed interval in a hypothesis test, it is crucial to highlight a fundamental aspect of our methodology. In our study, we opted for a Bayes Factor analysis for superiority design [5], aiming to assess whether the alternative hypothesis is greater than the null hypothesis (rather than simply being different from it). Indeed, as stated in our work, “the research question of interest ... was whether there is a significant difference in the primary endpoint (CDR-SB) favoring lecanemab at 18 months” [1]. From a methodological point of view, a superiority design inherently requires a one-tailed test [5], thus necessitating the utilization of a standard error set at 0.22.

    We are grateful to the author for affording us the opportunity to elucidate why and how we arrived at the estimation of the standard error of 0.22 in our study. In essence, our comment underscores the validity of our results within the framework of the design system we employed.

    Tommaso Costaa,b,c, Enrico Premid, Donato Liloiaa,b, Franco Caudaa,b,c, Jordi Manuelloa,b
    aGCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy bFOCUSLAB, Department of Psychology, University of Turin, Turin, Italy
    cNeuroscience Institute of Turin, Turin, Italy
    dStroke Unit, Department of Neurological and Vision Sciences, ASST Spedali Civili, Brescia, Italy

    Conflict of Interest
    None

    References
    [1]    Costa T, Premi E, Liloia D, Cauda F, Manuello J (2023) Unleashing the power of Bayesian re-analysis: enhancing insights into lecanemab (Clarity AD) phase III trial through informed t-test. J Alzheimers Dis 95, 1059-1065.
    [2]    Costa T, Cauda F (2022) A Bayesian reanalysis of the phase III aducanumab (ADU) trial. J Alzheimers Dis 87, 1009–1012.
    [3]    van Dyck CH, Swanson CJ, Aisen P, Bateman RJ, Chen C, Gee M, Kanekiyo M, Li D, Reyderman L, Cohen S, Froelich L, Katayama S, Sabbagh M, Vellas B, Watson D, Dhadda S, Irizarry M, Kramer LD, Iwatsubo T (2023) Lecanemab in early Alzheimer’s disease. N Engl J Med 388, 9–21.
    [4]    Higgins JP, Thomas J, Chandler J, Cumpston M, Li T, Page M, Welch VA (2019) Cochrane handbook for systematic reviews of interventions, John Wiley & Sons.
    [5]    van Ravenzwaaij D, Monden R, Tendeiro JN, Ioannidis JP (2019) Bayes factors for superiority, non-inferiority, and equivalence designs. BMC Med Res Methodol 19, 71.

  • Reply to: Comment on The MedWalk Randomized Controlled Trial Experimental Protocol   3 months 6 days ago

    We thank the author of the Letter to the Editor for commenting on our recently published paper, “A Mediterranean Diet and Walking Intervention to Reduce Cognitive Decline and Dementia Risk in Independently Living Older Australians: The MedWalk Randomized Controlled Trial Experimental Protocol, Including COVID-19 Related Modifications and Baseline Characteristics”. We provide responses to the comments made.

    In relation to the “representativeness of their sample,” Table 3 shows basic baseline characteristics of our cohort, including ethnicity, which is representative of the participants volunteering for this trial through the 17 retirement villages and 4 community-dwelling clusters established for recruitment. We agree that this cohort is not representative of the general Australian community; a limitation we will discuss when the findings of this trial are reported. This is a common issue globally with the lack of representation from minority groups in dietary and lifestyle intervention trials highlighting a need for specific recruitment strategies to ensure there is representation from all populations [1].

    Contrary to what has been suggested, we are not using the MMSE in "the assessment of dementia or mild cognitive impairment (MCI)." Rather we are using the MMSE to screen for cognitive impairment - to exclude any participants who may have dementia or MCI. The intended sample are independently living, cognitively healthy individuals. This MMSE screening is in addition to our exclusion criteria, of people who have already been diagnosed with dementia or other forms of cognitive impairment. We reported in Table 3 that MMSE is 28.9/30 with a standard deviation of 1.2, clearly above the MMSE threshold for cognitive impairment. Moreover, our primary outcome is cognition, using CANTAB cognitive tests that will be far more sensitive than any screening tools. In the unlikely event that an individual with dementia or MCI has been recruited, they are likely to be identified as an outlier in the data screening stage when analyzing these cognitive tests.

    In relation to the comment made about retirement villages versus community clusters, as stated in our paper and detailed in the CONSERVE - spirit checklist, additional recruitment through four community clusters was undertaken because of COVID-related impacts. However, recruitment through the wider community utilized the same inclusion and exclusion criteria such as the requirement to be living alone or with their partner and, as was the case for retirement villages, couples were assigned to the same group.

    We also stated that any significant differences between community/retirement villages will be investigated. Our approach will be as follows: i) A comparison of baseline values for the community and retirement village participants will be conducted for all the outcome measures and demographic characteristics. If no significant differences are found, we will treat as a combined sample. If not, we will control for a binary variable discriminating between community and retirement village participants (Community/Retirement Village Living) in all our outcome analyses. ii) In addition, we will test for a significant interaction effect for treatment*(Community/Retirement Village Living) in order to determine whether the treatment effect differs significantly for those living in the community and those living in retirement villages. If this interaction effect is found to be significant, marginal treatment means will be reported for community and Retirement Village Living participants. In addition, separate outcomes analyses will be performed for people living in retirement villages and people living in the community in order to validate the results.

    Lastly, with regards to the attrition rate of 7% and statement that "the authors need to consider a very robust protocol of adherence to maintain this low attrition rate." To clarify, we are not setting ourselves a goal to reduce attrition from 30% to 7%, rather we had already achieved this at the time of publication of our protocol paper, with approximately three quarters of data collection completed. This much lower than expected attrition rate as well as other factors including: a reduced number of assessments per participant (5 to 3) and a reduced number of participants per cluster (13 to 7) meant that the trial was still adequately powered (see "Statistical Analysis" Section).

    Andrew Pipingas, Karen J. Murphy, Courtney R. Davis, Catherine Itsiopoulos, Michael Kingsley, Andrew Scholey, Helen Macpherson, Leonie Segal, Jeff Breckon, Anne-Marie Minihane, Denny Meyer, Edward Ogden, Kathryn A. Dyer, Emily Eversteyn, Roy J. Hardman, Kaylass Poorun, Keri Justice, Maher Hana, Jonathan D. Buckley, David White, Kade Davison, Jessie S. Clark, Ella L. Bracci, and Greg Kennedy on behalf of MedWalk collaborative team

    [1] Shaw AR, Perales-Puchalt J, Johnson E, Espinoza-Kissell P, Acosta-Rullan M, Frederick S, Lewis A, Chang H, Mahnken J, Vidoni ED (2022) Representation of racial and ethnic minority populations in dementia prevention trials: a systematic review. J Prev Alzheimers Dis 9, 113-118.