| Literature DB >> 34632301 |
Timothy Daly1, Marion Houot2,3, Anouk Barberousse1, Amélie Petit4, Stéphane Epelbaum2,3.
Abstract
BACKGROUND: Therapeutic research into Alzheimer's disease (AD) has been dominated by the amyloid cascade hypothesis (ACH) since the 1990s. However, targeting amyloid in AD patients has not yet resulted in highly significant disease-modifying effects. Furthermore, other promising theories of AD etiology exist.Entities:
Keywords: Alzheimer’s disease; amyloid-β ; dementia prevention; diversity in science; gender; lifestyle factors; lifestyle interventions; pharmaceutical industry; tau protein; women in science
Year: 2021 PMID: 34632301 PMCID: PMC8461732 DOI: 10.3233/ADR-210030
Source DB: PubMed Journal: J Alzheimers Dis Rep ISSN: 2542-4823
Fig. 1A decision tree revealing pro-ACH/non-ACH differences according to the participant’s view on whether or not there is problematic adherence to the ACH. We cut the depth of the tree to 5. Leave nodes (i.e., the final node, colored in the figure) present the number of pro-ACH participants on the right and the number of non-ACH participants on the left. They are light blue to dark blue as a function of the proportion of non-ACH in the leave node, or they are light green to dark green as a function of the proportion of pro-ACH in the leave node. In the non-ACH group, 63 participants (47.37%) not identifying as male argue that there is problematic adherence to the ACH, compared to only 7 (18.42%) of the pro-ACH group with these characteristics. Conversely, on the other end of the scale, 6 males (or preferred not to say) of the pro-ACH group (15.79%) argued that there was no problematic adherence to the ACH and had more than 113 median publications. None of the non-ACH had this profile.
Differences in the constitutive characteristics and opinions towards the ACH of pro-ACH and non-ACH groups identified in the 173 survey participants. Gender differences were significant between the pro-ACH and non-ACH groups, with significantly more men being pro-ACH. Taken together, these results suggest an association between having pro-ACH opinions and more publications, industry money, and self-identifying as a key opinion leader. ‡Fisher’s exact test was used to compare groups for categorical variables
| All | Non-ACH | Pro-ACH |
| |
| N = 173 | N = 133 | N = 38 | ||
| (76.88%) | (21.97%) | |||
| Age > 60 y | 19 (11.05%) | 10 (7.52%) | 8 (21.05%) | 0.031* |
| Gender | 0.035* | |||
| | 83 (49.70%) | 71 (55.47%) | 12 (31.58%) | |
| | 80 (47.90%) | 54 (42.19%) | 25 (65.79%) | |
| | 3 (1.80%) | 2 (1.56%) | 1 (2.63%) | |
| | 1 (0.60%) | 1 (0.78%) | 0 (0.00%) | |
| Continent of Major Affiliation | 0.243 | |||
| | 1 (0.60%) | 0 (0.00%) | 0 (0.00%) | |
| | 101 (60.12%) | 78 (60.47%) | 23 (60.53%) | |
| | 11 (6.55%) | 10 (7.75%) | 1 (2.63%) | |
| | 9 (5.36%) | 9 (6.98%) | 0 (0.00%) | |
| | 40 (23.81%) | 28 (21.71%) | 12 (31.58%) | |
| | 6 (3.57%) | 4 (3.10%) | 2 (5.26%) | |
| Publications number > 100 | 24 (14.04%) | 14 (10.53%) | 10 (27.03%) | 0.016* |
| Profession | ||||
| | 67 (38.73%) | 51 (38.35%) | 15 (39.47%) | 0.236 |
| | 18 (10.40%) | 16 (12.03%) | 1 (2.63%) | |
| | 88 (50.87%) | 66 (49.62%) | 22 (57.89%) | |
| Key Opinion Leader (Yes) | 26 (15.48%) | 16 (12.40%) | 10 (26.32%) | 0.045* |
| Received money from pharma company (Yes) | 29 (16.86%) | 18 (13.53%) | 11 (28.95%) | 0.047* |
|
| ||||
|
|
|
|
| < |
|
|
|
| < | |
| There is problematic adherence to the ACH from either industry, academia, associations or funding bodies | 125 (73.96%) | 105 (80.15%) | 20 (54.05%) | 0.002* |
| Moving forwards (2019–), the ACH is a useful tool to guide research. | 60 (35.50%) | 35 (26.92%) | 24 (63.16%) | < 0.001* |
| Agree with Tanzi (2015): “The clinical trials are failing the hypothesis, the hypothesis is not failing the trial.” | 76 (44.71%) | 45 (34.35%) | 30 (78.95%) | < 0.001* |
| Agree with Tanzi (2017): “we need to find people with amyloid buildup on their brain early” and target it. | 89 (52.35%) | 56 (42.75%) | 32 (84.21%) | < 0.001* |
| Agree with Davies (2016): “we’re flogging a dead horse” (A-beta) | 54 (31.76%) | 52 (39.69%) | 2 (5.26%) | < 0.001* |
| Agree with Herrup (2015): “clinging to an inaccurate disease model is the option we should fear most.” | 82 (48.52%) | 75 (57.69%) | 7 (18.42%) | < 0.001* |
The popular vote of all researchers (pro-ACH and non-ACH taken together) toward therapeutic priorities in AD research, tabulated according to participants’ gender. Concerning pharmacological treatments, anti-tau drugs offered more optimism than drug classes inspired by the ACH (anti-Aβ antibodies and/or BACE inhibitors). The top three therapeutic targets at preclinical, prodromal, and established AD were also investigated. Lifestyle interventions were a top-3 therapeutic priority at all stages of AD. Taken as a whole, the data suggest a favorable opinion regarding lifestyle factors and tau protein intervention. Gender differences in therapeutic priority were only significant for preclinical AD, with significantly more males arguing in favor of anti-Aβ strategies at this stage. ‡Fisher’s exact test was used to compare groups for categorical variables
| All | Female | Male |
| |
| N = 173 | N = 83 | N = 80 | ||
| (49.70%) | (47.90%) | |||
|
| ||||
| Anti-tau | 97 (61.01%) | 50 (66.67%) | 40 (53.33%) | 0.133 |
| Anti-AB antibodies | 62 (38.99%) | 24 (32.00%) | 33 (44.00%) | 0.178 |
| BACE inhibitors | 31 (19.50%) | 15 (20.00%) | 12 (16.00%) | 0.671 |
| # | 0.020* | |||
| Lifestyle factors (diet, smoking, etc.) |
| 39 (46.99%) | 31 (39.74%) | |
| Aβ physiology (production, clearance, etc.) | 33 (19.41%) | 10 (12.05%) | 22 (28.21%) | |
| Inflammation, Microglia, and Astrocytes | 22 (12.94%) | 10 (12.05%) | 11 (14.10%) | |
| # | 0.060 | |||
| Lifestyle factors (diet, smoking, etc.) |
| 24 (32.00%) | 22 (29.73%) | |
| Tau and NFTs | 40 (25.32%) | 22 (29.33%) | 15 (20.27%) | |
| Inflammation |
| 13 (17.33%) | 11 (14.86%) | |
| # | 0.928 | |||
| Tau and NFTs | 44 (28.21%) | 19 (25.68%) | 21 (28.38%) | |
| Lifestyle factors (diet, smoking, etc.) | 38 (24.36%) | 20 (27.03%) | 17 (22.97%) | |
| Inflammation, Microglia, and Astrocytes | 29 (18.59%) | 14 (18.92%) | 13 (17.57%) |