Artificial Intelligence-Aided Precision Medicine for COVID-19: Strategic Areas of Research and Development.

Artificial intelligence (AI) technologies can play a key role in preventing, detecting, and monitoring epidemics. In this paper, we provide an overview of the recently published literature on the COVID-19 pandemic in four strategic areas: (1) triage, diagnosis, and risk prediction; (2) drug repurposing and development; (3) pharmacogenomics and vaccines; and (4) mining of the medical literature. We highlight how AI-powered health care can enable public health systems to efficiently handle future outbreaks and improve patient outcomes.

Sex and gender considerations in Alzheimer's disease: The Women's Brain Project contribution.

The global population is expected to have about 131.5 million people living with Alzheimer's disease (AD) and other dementias by 2050, posing a severe health crisis. Dementia is a progressive neurodegenerative condition that gradually impairs physical and cognitive functions. Dementia has a variety of causes, symptoms, and heterogeneity concerning the influence of sex on prevalence, risk factors, and outcomes. The proportion of male-to-female prevalence varies based on the type of dementia. Despite some types of dementia being more common in men, women have a greater lifetime risk of developing dementia. AD is the most common form of dementia in which approximately two-thirds of the affected persons are women. Profound sex and gender differences in physiology and pharmacokinetic and pharmacodynamic interactions have increasingly been identified. As a result, new approaches to dementia diagnosis, care, and patient journeys should be considered. In the heart of a rapidly aging worldwide population, the Women's Brain Project (WBP) was born from the necessity to address the sex and gender gap in AD. WBP is now a well-established international non-profit organization with a global multidisciplinary team of experts studying sex and gender determinants in the brain and mental health. WBP works with different stakeholders worldwide to help change perceptions and reduce sex biases in clinical and preclinical research and policy frameworks. With its strong female leadership, WBP is an example of the importance of female professionals' work in the field of dementia research. WBP-led peer-reviewed papers, articles, books, lectures, and various initiatives in the policy and advocacy space have profoundly impacted the community and driven global discussion. WBP is now in the initial phases of establishing the world's first Sex and Gender Precision Medicine Institute. This review highlights the contributions of the WBP team to the field of AD. This review aims to increase awareness of potentially important aspects of basic science, clinical outcomes, digital health, policy framework and provide the research community with potential challenges and research suggestions to leverage sex and gender differences. Finally, at the end of the review, we briefly touch upon our progress and contribution toward sex and gender inclusion beyond Alzheimer's disease.

Digital biomarkers and sex impacts in Alzheimer's disease management - potential utility for innovative 3P medicine approach.

Digital biomarkers are defined as objective, quantifiable physiological and behavioral data that are collected and measured by means of digital devices. Their use has revolutionized clinical research by enabling high-frequency, longitudinal, and sensitive measurements. In the field of neurodegenerative diseases, an example of a digital biomarker-based technology is instrumental activities of daily living (iADL) digital medical application, a predictive biomarker of conversion from mild cognitive impairment (MCI) due to Alzheimer's disease (AD) to dementia due to AD in individuals aged 55 + . Digital biomarkers show promise to transform clinical practice. Nevertheless, their use may be affected by variables such as demographics, genetics, and phenotype. Among these factors, sex is particularly important in Alzheimer's, where men and women present with different symptoms and progression patterns that impact diagnosis. In this study, we explore sex differences in Altoida's digital medical application in a sample of 568 subjects consisting of a clinical dataset (MCI and dementia due to AD) and a healthy population. We found that a biological sex-classifier, built on digital biomarker features captured using Altoida's application, achieved a 75% ROC-AUC (receiver operating characteristic - area under curve) performance in predicting biological sex in healthy individuals, indicating significant differences in neurocognitive performance signatures between males and females. The performance dropped when we applied this classifier to more advanced stages on the AD continuum, including MCI and dementia, suggesting that sex differences might be disease-stage dependent. Our results indicate that neurocognitive performance signatures built on data from digital biomarker features are different between men and women. These results stress the need to integrate traditional approaches to dementia research with digital biomarker technologies and personalized medicine perspectives to achieve more precise predictive diagnostics, targeted prevention, and customized treatment of cognitive decline. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-022-00284-3.

Investing in Late-Life Brain Capital.

Within many societies and cultures around the world, older adults are too often undervalued and underappreciated. This exacerbates many key challenges that older adults may face. It also undermines the many positive aspects of late life that are of tremendous value at both an individual and societal level. We propose a new approach to elevate health and well-being in late life by optimizing late-life Brain Capital. This form of capital prioritizes brain skills and brain health in a brain economy, which the challenges and opportunities of the 21st-century demands. This approach incorporates investing in late-life Brain Capital, developing initiatives focused on building late-life Brain Capital.

Simulating SARS-CoV-2 epidemics by region-specific variables and modeling contact tracing app containment.

Targeted contact-tracing through mobile phone apps has been proposed as an instrument to help contain the spread of COVID-19 and manage the lifting of nation-wide lock-downs currently in place in USA and Europe. However, there is an ongoing debate on its potential efficacy, especially in light of region-specific demographics. We built an expanded SIR model of COVID-19 epidemics that accounts for region-specific population densities, and we used it to test the impact of a contact-tracing app in a number of scenarios. Using demographic and mobility data from Italy and Spain, we used the model to simulate scenarios that vary in baseline contact rates, population densities, and fraction of app users in the population. Our results show that, in support of efficient isolation of symptomatic cases, app-mediated contact-tracing can successfully mitigate the epidemic even with a relatively small fraction of users, and even suppress altogether with a larger fraction of users. However, when regional differences in population density are taken into consideration, the epidemic can be significantly harder to contain in higher density areas, highlighting potential limitations of this intervention in specific contexts. This work corroborates previous results in favor of app-mediated contact-tracing as mitigation measure for COVID-19, and draws attention on the importance of region-specific demographic and mobility factors to achieve maximum efficacy in containment policies.

Sex differences in Alzheimer disease - the gateway to precision medicine.

Alzheimer disease (AD) is characterized by wide heterogeneity in cognitive and behavioural syndromes, risk factors and pathophysiological mechanisms. Addressing this phenotypic variation will be crucial for the development of precise and effective therapeutics in AD. Sex-related differences in neural anatomy and function are starting to emerge, and sex might constitute an important factor for AD patient stratification and personalized treatment. Although the effects of sex on AD epidemiology are currently the subject of intense investigation, the notion of sex-specific clinicopathological AD phenotypes is largely unexplored. In this Review, we critically discuss the evidence for sex-related differences in AD symptomatology, progression, biomarkers, risk factor profiles and treatment. The cumulative evidence reviewed indicates sex-specific patterns of disease manifestation as well as sex differences in the rates of cognitive decline and brain atrophy, suggesting that sex is a crucial variable in disease heterogeneity. We discuss critical challenges and knowledge gaps in our current understanding. Elucidating sex differences in disease phenotypes will be instrumental in the development of a 'precision medicine' approach in AD, encompassing individual, multimodal, biomarker-driven and sex-sensitive strategies for prevention, detection, drug development and treatment.