Donanemab, another anti-Alzheimer's drug with risk and uncertain benefit.

Based on "reducing amyloid plaques in the brain", the U.S. Food and Drug Administration has granted accelerated and full approval for two monoclonal anti-Alzheimer's antibodies, aducanumab and lecanemab, respectively. Approval of a third antibody, donanemab, is pending. Moreover, lecanemab and donanemab are claimed to cause delay in the cognitive decline that characterizes the disease. We believe that these findings are subject to misinterpretation and statistical bias. Donanemab is claimed to cause removal of up to 86 % of cerebral amyloid and 36 % delay in cognitive decline compared to placebo. In reality, these are very small changes on an absolute scale and arguably less than what can be achieved with cholinesterase inhibitor/memantine therapy. Moreover, the "removal" of amyloid, based on the reduced accumulation of amyloid-PET tracer, most likely also reflects therapy-related tissue damage. This would also correlate with the minimal clinical effect, the increased frequency of amyloid-related imaging abnormalities, and the accelerated loss of brain volume in treated compared to placebo patients observed with these antibodies. We recommend halting approvals of anti-AD antibodies until these issues are fully understood to ensure that antibody treatment does not cause more harm than benefit to patients.

Panel stacking is a threat to consensus statement validity.

Consensus statements can be very influential in medicine and public health. Some of these statements use systematic evidence synthesis but others fail on this front. Many consensus statements use panels of experts to deduce perceived consensus through Delphi processes. We argue that stacking of panel members towards one particular position or narrative is a major threat, especially in absence of systematic evidence review. Stacking may involve financial conflicts of interest, but non-financial conflicts of strong advocacy can also cause major bias. Given their emerging importance, we describe here how such consensus statements may be misleading, by analysing in depth a recent high-impact Delphi consensus statement on COVID-19 recommendations as a case example. We demonstrate that many of the selected panel members and at least 35% of the core panel members had advocated towards COVID-19 elimination (zero-COVID) during the pandemic and were leading members of aggressive advocacy groups. These advocacy conflicts were not declared in the Delphi consensus publication, with rare exceptions. Therefore, we propose that consensus statements should always require rigorous evidence synthesis and maximal transparency on potential biases towards advocacy or lobbyist groups to be valid. While advocacy can have many important functions, its biased impact on consensus panels should be carefully avoided.

Excess mortality in Denmark, Finland, Norway and Sweden during the COVID-19 pandemic 2020-2022.

BACKGROUND: The Nordic countries represent a unique case study for the COVID-19 pandemic due to socioeconomic and cultural similarities, high-quality comparable administrative register data and notable differences in mitigation policies during the pandemic. We aimed to compare weekly excess mortality in the Nordic countries across the three full pandemic years 2020-2022. METHODS: Using data on weekly all-cause mortality from official administrative registers in Denmark, Finland, Norway and Sweden, we employed time series regression models to assess mortality developments within each pandemic year, with the period 2010-2019 used as reference period. We then compared excess mortality across the countries in 2020-2022, taking differences in population size and age- and sex-distribution into account. Results were age- and sex-standardized to the Danish population of 2020. Robustness was examined with a variety of sensitivity analyses. RESULTS: While Sweden experienced excess mortality in 2020 [75 excess deaths per 100 000 population (95% prediction interval 29-122)], Denmark, Finland and Norway experienced excess mortality in 2022 [52 (14-90), 130 (83-177) and 88 (48-128), respectively]. Weekly death data reveal how mortality started to increase in mid-2021 in Denmark, Finland and Norway, and continued above the expected level through 2022. CONCLUSION: Although the Nordic countries experienced relatively low pandemic excess mortality, the impact and timing of excess mortality differed substantially. These estimates-arguably the most accurate available for any region in capturing pandemic-related excess deaths-may inform future research and policy regarding the complex mortality dynamics in times of a health crisis such as the COVID-19 pandemic.

Recalibrating the Risk-Benefit Profiles of Lecanemab and Donanemab: Scales, Immunoreactivity, and Changes in Amyloid-ß42.

Three recent anti-amyloid-ß antibody trials for Alzheimer's disease reported similar effect sizes, used non-reactive saline as placebo, and showed large numbers of adverse events including imaging anomalies (ARIA) that correlate with cognitive changes. Conversely, all previous antibody trials were less reactive and pronounced ineffective. We argue that these observations point to unblinding bias, inflating apparent efficacy and thus altering the risk-benefit balance. Further, we highlight data demonstrating that beyond reducing amyloid, monoclonal antibodies increase monomeric amyloid-ß42 in cerebrospinal fluid, which may explain potential benefits. We should recalibrate the efficacy of these antibodies and devote more resources into strategies beyond removing amyloid.

Revision of Alzheimer's diagnostic criteria or relocation of the Potemkin village.

The recently announced revision of the Alzheimer's disease (AD) diagnostic ATN classification adds to an already existing disregard for clinical assessment the rejection of image-based in vivo assessment of the brain's condition. The revision suggests that the diagnosis of AD should be based solely on the presence of cerebral amyloid-beta and tau, indicated by the "A" and "T". The "N", which stands for neurodegeneration - detected by imaging - should no longer be given importance, except that A+ ± T + = AD with amyloid PET being the main method for demonstrating A+ . We believe this is an artificial and misleading suggestion. It is artificial because it relies on biomarkers whose significance remains obscure and where the detection of "A" is based on a never-validated PET method using a tracer that marks much more than amyloid-beta. It is misleading because many patients without dementia will be falsely classified as having AD, but nonetheless candidates for passive immunotherapy, which may be more harmful than beneficial, and sometimes fatal.

Policies on children and schools during the SARS-CoV-2 pandemic in Western Europe.

During the pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), mitigation policies for children have been a topic of considerable uncertainty and debate. Although some children have co-morbidities which increase their risk for severe coronavirus disease (COVID-19), and complications such as multisystem inflammatory syndrome and long COVID, most children only get mild COVID-19. On the other hand, consistent evidence shows that mass mitigation measures had enormous adverse impacts on children. A central question can thus be posed: What amount of mitigation should children bear, in response to a disease that is disproportionally affecting older people? In this review, we analyze the distinct child versus adult epidemiology, policies, mitigation trade-offs and outcomes in children in Western Europe. The highly heterogenous European policies applied to children compared to adults did not lead to significant measurable differences in outcomes. Remarkably, the relative epidemiological importance of transmission from school-age children to other age groups remains uncertain, with current evidence suggesting that schools often follow, rather than lead, community transmission. Important learning points for future pandemics are summarized.

Passive Alzheimer's immunotherapy: A promising or uncertain option?

The US Food and Drug Administration (FDA)'s recent accelerated approval of two anti-amyloid antibodies for treatment of Alzheimer's disease (AD), aducanumab and lecanemab, has caused substantial debate. To inform this debate, we reviewed the literature on randomized clinical trials conducted with eight such antibodies focusing on clinical efficacy, cerebral amyloid removal, amyloid-related imaging abnormalities (ARIAs) and cerebral volumes to the extent such measurements have been reported. Two antibodies, donanemab and lecanemab, have demonstrated clinical efficacy, but these results remain uncertain. We further argue that the decreased amyloid PET signal in these trials is unlikely to be a one-to-one reflection of amyloid removal, but rather a reflection of increased therapy-related brain damage, as supported by the increased incidence of ARIAs and reported loss of brain volume. Due to these uncertainties of benefit and risk, we recommend that the FDA pauses existing approvals and approval of new antibodies until results of phase 4 studies with these drugs are available to inform on these risk-benefit uncertainties. We recommend that the FDA prioritize FDG PET and detection of ARIAs and accelerated brain volume loss with MRI in all trial patients, and neuropathological examination of all patients who die in these phase 4 trials.

FDG-PET versus Amyloid-PET Imaging for Diagnosis and Response Evaluation in Alzheimer's Disease: Benefits and Pitfalls.

In June 2021, the US Federal Drug and Food Administration (FDA) granted accelerated approval for the antibody aducanumab and, in January 2023, also for the antibody lecanemab, based on a perceived drug-induced removal of cerebral amyloid-beta as assessed by amyloid-PET and, in the case of lecanemab, also a presumption of limited clinical efficacy. Approval of the antibody donanemab is awaiting further data. However, published trial data indicate few, small and uncertain clinical benefits, below what is considered "clinically meaningful" and similar to the effect of conventional medication. Furthermore, a therapy-related decrease in the amyloid-PET signal may also reflect increased cell damage rather than simply "amyloid removal". This interpretation is more consistent with increased rates of amyloid-related imaging abnormalities and brain volume loss in treated patients, relative to placebo. We also challenge the current diagnostic criteria for AD based on amyloid-PET imaging biomarkers and recommend that future anti-AD therapy trials apply: (1) diagnosis of AD based on the co-occurrence of cognitive decline and decreased cerebral metabolism assessed by FDA-approved FDG-PET, (2) therapy efficacy determined by favorable effect on cognitive ability, cerebral metabolism by FDG-PET, and brain volumes by MRI, and (3) neuropathologic examination of all deaths occurring in these trials.

The Anti-Amyloid Monoclonal Antibody Lecanemab: 16 Cautionary Notes.

After the CLARITY-AD clinical trial results of lecanemab were interpreted as positive, and supporting the amyloid hypothesis, the drug received accelerated Food and Drug Administration approval. However, we argue that benefits of lecanemab treatment are uncertain and may yield net harm for some patients, and that the data do not support the amyloid hypothesis. We note potential biases from inclusion, unblinding, dropouts, and other issues. Given substantial adverse effects and subgroup heterogeneity, we conclude that lecanemab's efficacy is not clinically meaningful, consistent with numerous analyses suggesting that amyloid-ß and its derivatives are not the main causative agents of Alzheimer's disease dementia.

The amyloid cascade hypothesis: an updated critical review.

Results from recent clinical trials of antibodies that target amyloid-ß (Aß) for Alzheimer's disease have created excitement and have been heralded as corroboration of the amyloid cascade hypothesis. However, while Aß may contribute to disease, genetic, clinical, imaging and biochemical data suggest a more complex aetiology. Here we review the history and weaknesses of the amyloid cascade hypothesis in view of the new evidence obtained from clinical trials of anti-amyloid antibodies. These trials indicate that the treatments have either no or uncertain clinical effect on cognition. Despite the importance of amyloid in the definition of Alzheimer's disease, we argue that the data point to Aß playing a minor aetiological role. We also discuss data suggesting that the concerted activity of many pathogenic factors contribute to Alzheimer's disease and propose that evolving multi-factor disease models will better underpin the search for more effective strategies to treat the disease.

The contribution of population age-sex structure to the excess mortality estimates of 2020-2021 in Denmark, Finland, Iceland, Norway, and Sweden.

The Nordic countries offer an ideal case study of the COVID-19 pandemic due to their comparability, high data quality, and variable mitigations. We investigated the age- and sex-specific mortality patterns during 2020-2021 for the five Nordic countries and analysed the total age- and sex-adjusted excess deaths, ratios of actual to expected death rates, and age-standardized excess death estimates. We assessed excess deaths using several time periods and sensitivity tests, and 42 sex and age groups. Declining pre-pandemic age-specific death rates reflected improving health demographics. These affect the expected death estimates and should be accounted for in excess mortality models. Denmark had the highest death rates both before and during the pandemic, whereas in 2020 Sweden had the largest mortality increase. The age-standardized mortality of Denmark, Iceland and Norway was lowest in 2020. 2021 was one of the lowest mortality years for all Nordic countries. The total excess deaths in 2020-2021 were dominated by 70-89-year-olds, were not identified in children, and were more pronounced among men than women. Sweden had more excess deaths in 2020 than in 2021, whereas Finland, Norway and Denmark had the opposite. Our study provides new details on Nordic sex- and age-specific mortality during the first two years of the pandemic and shows that several metrics are important to enable a full understanding and comparison of the pandemic mortality.

Stability and expression of SARS-CoV-2 spike-protein mutations.

Protein fold stability likely plays a role in SARS-CoV-2 S-protein evolution, together with ACE2 binding and antibody evasion. While few thermodynamic stability data are available for S-protein mutants, many systematic experimental data exist for their expression. In this paper, we explore whether such expression levels relate to the thermodynamic stability of the mutants. We studied mutation-induced SARS-CoV-2 S-protein fold stability, as computed by three very distinct methods and eight different protein structures to account for method- and structure-dependencies. For all methods and structures used (24 comparisons), computed stability changes correlate significantly (99% confidence level) with experimental yeast expression from the literature, such that higher expression is associated with relatively higher fold stability. Also significant, albeit weaker, correlations were seen between stability and ACE2 binding effects. The effect of thermodynamic fold stability may be direct or a correlate of amino acid or site properties, notably the solvent exposure of the site. Correlation between computed stability and experimental expression and ACE2 binding suggests that functional properties of the SARS-CoV-2 S-protein mutant space are largely determined by a few simple features, due to underlying correlations. Our study lends promise to the development of computational tools that may ideally aid in understanding and predicting SARS-CoV-2 S-protein evolution.

The proteinopenia hypothesis: Loss of Aß42 and the onset of Alzheimer's Disease.

The dominant protein-lowering strategy in Alzheimer's Disease (AD) has failed to provide a clinically-meaningful treatment for patients. We hypothesize that the loss of functional, soluble Aß42 during the process of aggregation into amyloid is more detrimental to the brain than the corresponding accrual of insoluble amyloid.

Estimates of excess mortality for the five Nordic countries during the COVID-19 pandemic 2020-2021.

BACKGROUND: Excess mortality during the COVID-19 pandemic is of major scientific and political interest. METHODS: We critically reviewed different estimates of all-cause excess mortality for the five Nordic countries (Denmark, Finland, Iceland, Norway and Sweden), which have been much studied during the COVID-19 pandemic, using the latest register data to discuss uncertainties and implications. RESULTS: We show using back-calculation of expected deaths from Nordic all-cause deaths that the Institute for Health Metrics and Evaluation model is a clear outlier in the compared estimates and likely substantially overestimates excess mortality of Finland and Denmark, and probably Sweden. Our review suggests a range of total Nordic excess deaths of perhaps 15 000-20 000, but results are sensitive to assumptions in the models as shown. CONCLUSIONS: We document substantial heterogeneity and uncertainty in estimates of excess mortality. All estimates should be taken with caution in their interpretation as they miss detailed account of demographics, such as changes in the age group populations over the study period.

Structural heterogeneity and precision of implications drawn from cryo-electron microscopy structures: SARS-CoV-2 spike-protein mutations as a test case.

Protein structures may be used to draw functional implications at the residue level, but how sensitive are these implications to the exact structure used? Calculation of the effects of SARS-CoV-2 S-protein mutations based on experimental cryo-electron microscopy structures have been abundant during the pandemic. To understand the precision of such estimates, we studied three distinct methods to estimate stability changes for all possible mutations in 23 different S-protein structures (3.69 million ΔΔG values in total) and explored how random and systematic errors can be remedied by structure-averaged mutation group comparisons. We show that computational estimates have low precision, due to method and structure heterogeneity making results for single mutations uninformative. However, structure-averaged differences in mean effects for groups of substitutions can yield significant results. Illustrating this protocol, functionally important natural mutations, despite individual variations, average to a smaller stability impact compared to other possible mutations, independent of conformational state (open, closed). In summary, we document substantial issues with precision in structure-based protein modeling and recommend sensitivity tests to quantify these effects, but also suggest partial solutions to the problem in the form of structure-averaged "ensemble" estimates for groups of residues when multiple structures are available.

Assessment of AlphaFold2 for Human Proteins via Residue Solvent Exposure.

As only 35% of human proteins feature (often partial) PDB structures, the protein structure prediction tool AlphaFold2 (AF2) could have massive impact on human biology and medicine fields, making independent benchmarks of interest. We studied AF2's ability to describe the backbone solvent exposure as a functionally important and easily interpretable "natural coordinate" of protein conformation, using human proteins as test case. After screening for appropriate comparative sets, we matched 1818 human proteins predicted by AF2 against 7585 unique experimental PDBs, and after curation for sequence overlap, we assessed 1264 comparative pairs comprising 115 unique AF2 structures and 652 unique experimental structures. AF2 performed markedly worse for multimers, whereas ligands, cofactors, and experimental resolution were interestingly not very important for performance. AF2 performed excellently for monomer proteins. Challenges relating to specific groups of residues and multimers were analyzed. We identified larger deviations for lower-confidence scores (pLDDT), and exposed residues and polar residues (e.g., Asp, Glu, Asn) being less accurately described than hydrophobic residues. Proline conformations were the hardest to predict, probably due to a common location in dynamic solvent-accessible parts. In summary, using solvent exposure as a metric, we quantified the performance of AF2 for human proteins and provided estimates of the expected agreement as a function of ligand presence, multimer/monomer status, local residue solvent exposure, pLDDT, and amino acid type. Overall performance was found to be excellent.

Data set and fitting dependencies when estimating protein mutant stability: Toward simple, balanced, and interpretable models.

Accurate prediction of protein stability changes upon mutation (ΔΔG) is increasingly important to evolution studies, protein engineering, and screening of disease-causing gene variants but is challenged by biases in training data. We investigated 45 linear regression models trained on data sets that account systematically for destabilization bias and mutation-type bias BM . The models were externally validated on three test data sets probing different pathologies and for internal consistency (symmetry and neutrality). Model structure and performance substantially depended on training data and even fitting method. We developed two final models: SimBa-IB for typical natural mutations and SimBa-SYM for situations where stabilizing and destabilizing mutations occur to a similar extent. SimBa-SYM, despite is simplicity, is essentially non-biased (vs. the Ssym data set) while still performing well for all data sets (R ~ 0.46-0.54, MAE = 1.16-1.24 kcal/mol). The simple models provide advantage in terms of interpretability, use and future improvement, and are freely available on GitHub.

Structure and Mutations of SARS-CoV-2 Spike Protein: A Focused Overview.

The spike protein (S-protein) of SARS-CoV-2, the protein that enables the virus to infect human cells, is the basis for many vaccines and a hotspot of concerning virus evolution. Here, we discuss the outstanding progress in structural characterization of the S-protein and how these structures facilitate analysis of virus function and evolution. We emphasize the differences in reported structures and that analysis of structure-function relationships is sensitive to the structure used. We show that the average residue solvent exposure in nearly complete structures is a good descriptor of open vs closed conformation states. Because of structural heterogeneity of functionally important surface-exposed residues, we recommend using averages of a group of high-quality protein structures rather than a single structure before reaching conclusions on specific structure-function relationships. To illustrate these points, we analyze some significant chemical tendencies of prominent S-protein mutations in the context of the available structures. In the discussion of new variants, we emphasize the selectivity of binding to ACE2 vs prominent antibodies rather than simply the antibody escape or ACE2 affinity separately. We note that larger chemical changes, in particular increased electrostatic charge or side-chain volume of exposed surface residues, are recurring in mutations of concern, plausibly related to adaptation to the negative surface potential of human ACE2. We also find indications that the fixated mutations of the S-protein in the main variants are less destabilizing than would be expected on average, possibly pointing toward a selection pressure on the S-protein. The richness of available structures for all of these situations provides an enormously valuable basis for future research into these structure-function relationships.

Precision Biotransformation of Emerging Pollutants by Human Cytochrome P450 Using Computational-Experimental Synergy: A Case Study of Tris(1,3-dichloro-2-propyl) Phosphate.

Precision biotransformation is an envisioned strategy offering detailed insights into biotransformation pathways in real environmental settings using experimentally guided high-accuracy quantum chemistry. Emerging pollutants, whose metabolites are easily overlooked but may cause idiosyncratic toxicity, are important targets of such a strategy. We demonstrate here that complex metabolic reactions of tris(1,3-dichloro-2-propyl) phosphate (TDCIPP) catalyzed by human CYP450 enzymes can be mapped via a three-step synergy strategy: (i) screening the possible metabolites via high-throughout (moderate-accuracy) computations; (ii) analyzing the proposed metabolites in vitro by human liver microsomes and recombinant human CYP450 enzymes; and (iii) rationalizing the experimental data via precise mechanisms using high-level targeted computations. Through the bilateral dialogues from qualitative to semi-quantitative to quantitative levels, we show how TDCIPP metabolism especially by CYP3A4 generates bis(1,3-dichloro-2-propyl) phosphate (BDCIPP) as an O-dealkylation metabolite and bis(1,3-dichloro-2-propyl) 3-chloro-1-hydroxy-2-propyl phosphate (alcoholß-dehalogen) as a dehalogenation/reduction metabolite via the initial rate-determining H-abstraction from αC- and ßC-positions. The relative yield ratio [dehalogenation/reduction]/[O-dealkylation] is derived from the relative barriers of H-abstraction at the ßC- and αC-positions by CYP3A4, estimated as 0.002 to 0.23, viz., an in vitro measured ratio of 0.04. Importantly, alcoholß-dehalogen formation points to a new mechanism involving successive oxidation and reduction functions of CYP450, with its precursor aldehydeß-dehalogen being a key intermediate detected by trapping assays and rationalized by computations. We conclude that the proposed three-step synergy strategy may meet the increasing challenge of elucidating biotransformation mechanisms of substantial synthesized organic compounds in the future.