Deep learning for cancer survival prediction

Cancer claimed 18.1 millions deaths worldwide in 2018 and $87.8 billion for health-care in 2014 in USA. The tremendous impact this disease supposes worldwide, combined with the increasingly availability of genomic and transcriptomic data, have aroused the interest on incorporating cutting edge technologies, such as Deep Learning (DL), in the fight against cancer. DL has stand out in the last years, particularly because of the performance of the Convolutional Neural Networks (ConvNets) models in image recognition. The problem for which all models in this project have been trained is the prediction of cancer survival in a discrete set of time intervals, from RNA-Seq data, because of the importance survival analysis have in the study of cancer treatment and its improvement. The very nature of biological data brings some inconvenients when using it for training a ConvNet model. These data are usually composed by a much bigger number of features (M) than observations (N). This is known as the Curse of Dimensionality (M>>N). Other inconvenient is the lack, a priori, of spatial information among biological features. ConvNet is a DL model which is specially designed for image processing, in which the pixels composing them are related to its neighbour. This relation is used by ConvNets to extract more knowledge from observations and have, in consequence, a better performance. This project proposes some strategies to try to solve these two inconvenients. In order to equip gene-expression-profiles with structure, five strategies have been proposed, applied and compared. Similarly, the transfer learning technique known as fine-tuning have been applied to try to solve the inconvenient which we refer to as the Curse of Dimensionality. The comparison of these models, all trained with the same set of features and observations, has been made by calculating the Concordance Index (C-index) metric for each of them.El cáncer se cobró 18,1 millones de muertes a nivel mundial en 2018 y$87,8 billones para cuidados de salud durante el año 2014 en EEUU. El tremendo impacto que esta enfermedad supone a nivel mundial, junto con la disponibilidad cada vez mayor de datos genómicos y transcriptómicos, han potenciado el interés en incorporar tecnologías de vanguardia, como es el Aprendizaje Profundo (AI), a la lucha contra el cáncer. AI ha destacado en los últimos años, particularmente por el rendimiento de los modelos de Redes Neuronales Convolucionales (RNC) en reconocimiento de imágenes. El problema para el cual todos los modelos de este proyecto han sido entrenados es la predicción de supervivencia en cáncer en un conjunto discreto de intervalos de tiempo a partir de datos de RNA-Seq, debido a la importancia que el análisis de la supervivencia tiene en cuanto al estudio de los tratamientos contra el cáncer y su mejora. La propia naturaleza de los datos biológicos trae consigo algunos inconvenientes cuando se usan para entrenar modelos de RNC. Estos datos normalmente est´an formados por un número mucho mayor de variables (M) que de observaciones (N). Esto se conoce como la maldición de la dimensionalidad (en inglés, the Curse of Dimensionality) (M>>N). Otro inconveniente es la falta, a priori, de información espacial entre las variables biológicas. RNC son un tipo de modelo concreto de Aprendizaje Profundo que está especialmente pensado para el procesado de imágenes, en las cuales los píxeles que las componen se relacionan con sus píxeles vecinos. Esta relación se usa en las RNC para extraer más conocimientos de las observaciones y tener, en consecuencia, un mejor rendimiento. En este proyecto se proponen algunas estrategias para tratar de resolver estos dos inconvenientes. Con el objetivo de equipar a los perfiles de expresión génica con estructura, cinco estrategias han sido propuestas, aplicadas y comparadas. ..

COVID-19 after two years: trajectories of different components of mental health in the Spanish population

Aims: Our study aimed to (1) identify trajectories on different mental health components during a two-year follow-up of the COVID-19 pandemic and contextualise them according to pandemic periods; (2) investigate the associations between mental health trajectories and several exposures, and determine whether there were differences among the different mental health outcomes regarding these associations. Methods: We included 5535 healthy individuals, aged 40–65 years old, from the Barcelona Brain Health Initiative (BBHI). Growth mixture models (GMM) were fitted to classify individuals into different trajectories for three mental health-related outcomes (psychological distress, personal growth and loneliness). Moreover, we fitted a multinomial regression model for each outcome considering class membership as the independent variable to assess the association with the predictors. Results: For the outcomes studied we identified three latent trajectories, differentiating two major trends, a large proportion of participants was classified into ‘resilient’ trajectories, and a smaller proportion into ‘chronic-worsening’ trajectories. For the former, we observed a lower susceptibility to the changes, whereas, for the latter, we noticed greater heterogeneity and susceptibility to different periods of the pandemic. From the multinomial regression models, we found global and cognitive health, and coping strategies as common protective factors among the studied mental health components. Nevertheless, some differences were found regarding the risk factors. Living alone was only significant for those classified into ‘chronic’ trajectories of loneliness, but not for the other outcomes. Similarly, secondary or higher education was only a risk factor for the ‘worsening’ trajectory of personal growth. Finally, smoking and sleeping problems were risk factors which were associated with the ‘chronic’ trajectory of psychological distress. Conclusions: Our results support heterogeneity in reactions to the pandemic and the need to study different mental health-related components over a longer follow-up period, as each one evolves differently depending on the pandemic period. In addition, the understanding of modifiable protective and risk factors associated with these trajectories would allow the characterisation of these segments of the population to create targeted interventions"This work was supported by a grant from the Agència de Gestió d'Ajuts Universitaris i de Recerca (AGAUR) ‘PANDÈMIES 2020’ (ref. 2020PANDE00043) and a grant from ‘La Marató de TV3’ MARATÓ 2020 COVID-19 (ref. 202129–31). Supported in part by the Spanish Ministry of Science, Innovation and Universities (MICIU/FEDER; grant number RTI2018-095181-B-C21) and an ICREA Academia 2019 grant award to D. B-F. Partially, this research has received funding from ‘La Caixa’ Foundation (grant number LCF/PR/PR16/11110004), and from Institut Guttmann and Fundació Abertis. I.B-M. was supported by a postdoctoral fellowship related to ‘PANDÈMIES 2020’ (AGAUR; 2020PANDE00043). D.F. has been supported by grant 2021 SGR 01421 (GRBIO) administrated by the Departament de Recerca I Universitats de la Generalitat de Catalunya (Spain) and by the Ministerio de Ciencia e Innovación (Spain) [PID2019-104830RB-I00/ DOI (AEI): 10.13039/501100011033].. J.M.T. was partly supported by AGAUR (2018 PROD 00172), Fundació Joan Ribas Araquistain and ‘La Marató de TV3’ Fundation (201735.10). This research was furthermore supported by the Government of Catalonia (2017SGR748). We also acknowledge support from the Spanish Ministry of Science and Innovation and State Research Agency through the ‘Centro de Excelencia Severo Ochoa 2019-2023’ Program (CEX2018-000806-S), and support from the Generalitat de Catalunya through the CERCA Program"Peer ReviewedPostprint (published version

COVID-19 after two years : trajectories of different components of mental health in the Spanish population

Our study aimed to (1) identify trajectories on different mental health components during a two-year follow-up of the COVID-19 pandemic and contextualise them according to pandemic periods; (2) investigate the associations between mental health trajectories and several exposures, and determine whether there were differences among the different mental health outcomes regarding these associations. We included 5535 healthy individuals, aged 40-65 years old, from the Barcelona Brain Health Initiative (BBHI). Growth mixture models (GMM) were fitted to classify individuals into different trajectories for three mental health-related outcomes (psychological distress, personal growth and loneliness). Moreover, we fitted a multinomial regression model for each outcome considering class membership as the independent variable to assess the association with the predictors. For the outcomes studied we identified three latent trajectories, differentiating two major trends, a large proportion of participants was classified into 'resilient' trajectories, and a smaller proportion into 'chronic-worsening' trajectories. For the former, we observed a lower susceptibility to the changes, whereas, for the latter, we noticed greater heterogeneity and susceptibility to different periods of the pandemic. From the multinomial regression models, we found global and cognitive health, and coping strategies as common protective factors among the studied mental health components. Nevertheless, some differences were found regarding the risk factors. Living alone was only significant for those classified into 'chronic' trajectories of loneliness, but not for the other outcomes. Similarly, secondary or higher education was only a risk factor for the 'worsening' trajectory of personal growth. Finally, smoking and sleeping problems were risk factors which were associated with the 'chronic' trajectory of psychological distress. Our results support heterogeneity in reactions to the pandemic and the need to study different mental health-related components over a longer follow-up period, as each one evolves differently depending on the pandemic period. In addition, the understanding of modifiable protective and risk factors associated with these trajectories would allow the characterisation of these segments of the population to create targeted interventions

Functional brain connectivity prior to the COVID-19 outbreak moderates the effects of coping and perceived stress on mental health changes. A first year of COVID-19 pandemic follow-up study.

Background: The COVID-19 pandemic provides a unique opportunity to investigate the psychological impact of a global major adverse situation. Our aim was to examine, in a longitudinal prospective study, the demographic, psychological, and neurobiological factors associated with interindividual differences in resilience to the mental health impact of the pandemic. Methods: We included 2023 healthy participants (age: 54.32 ± 7.18 years, 65.69% female) from the Barcelona Brain Health Initiative cohort. A linear mixed model was used to characterize the change in anxiety and depression symptoms based on data collected both pre-pandemic and during the pandemic. During the pandemic, psychological variables assessing individual differences in perceived stress and coping strategies were obtained. In addition, in a subsample (n = 433, age 53.02 ± 7.04 years, 46.88% female) with pre-pandemic resting-state functional magnetic resonance imaging available, the system segregation of networks was calculated. Multivariate linear models were fitted to test associations between COVID-19-related changes in mental health and demographics, psychological features, and brain network status. Results: The whole sample showed a general increase in anxiety and depressive symptoms after the pandemic onset, and both age and sex were independent predictors. Coping strategies attenuated the impact of perceived stress on mental health. The system segregation of the frontoparietal control and default mode networks were found to modulate the impact of perceived stress on mental health. Conclusions: Preventive strategies targeting the promotion of mental health at the individual level during similar adverse events in the future should consider intervening on sociodemographic and psychological factors as well as their interplay with neurobiological substrates

Neuromodulation-induced prehabilitation to leverage neuroplasticity before brain tumor surgery: a single-cohort feasibility trial protocol

IntroductionNeurosurgery for brain tumors needs to find a complex balance between the effective removal of targeted tissue and the preservation of surrounding brain areas. Neuromodulation-induced cortical prehabilitation (NICP) is a promising strategy that combines temporary inhibition of critical areas (virtual lesion) with intensive behavioral training to foster the activation of alternative brain resources. By progressively reducing the functional relevance of targeted areas, the goal is to facilitate resection with reduced risks of neurological sequelae. However, it is still unclear which modality (invasive vs. non-invasive neuromodulation) and volume of therapy (behavioral training) may be optimal in terms of feasibility and efficacy.Methods and analysisPatients undertake between 10 and 20 daily sessions consisting of neuromodulation coupled with intensive task training, individualized based on the target site and neurological functions at risk of being compromised. The primary outcome of the proposed pilot, single-cohort trial is to investigate the feasibility and potential effectiveness of a non-invasive NICP protocol on neuroplasticity and post-surgical outcomes. Secondary outcomes investigating longitudinal changes (neuroimaging, neurophysiology, and clinical) are measured pre-NICP, post-NICP, and post-surgery.Ethics and disseminationEthics approval was obtained from the Research Ethical Committee of Fundació Unió Catalana d'Hospitals (approval number: CEI 21/65, version 1, 13/07/2021). The results of the study will be submitted to a peer-reviewed journal and presented at scientific congresses.Clinical trial registrationClinicalTrials.gov, identifier NCT05844605

Purpose in life promotes resilience to age‑related brain burden in middle‑aged adults

Disease‑modifying agents to counteract cognitive impairment in older age remain elusive. Hence, identifying modifiable factors promoting resilience, as the capacity of the brain to maintain cognition and function with aging and disease, is paramount. In Alzheimer’s disease (AD), education and occupation are typical cognitive reserve proxies. However, the importance of psychological factors is being increasingly recognized, as their operating biological mechanisms are elucidated. Purpose in life (PiL), one of the pillars of psychological well‑being, has previously been found to reduce the deleterious effects of AD‑related pathological changes on cognition. However, whether PiL operates as a resilience factor in middle‑aged individuals and what are the underlying neural mechanisms remain unknown.Medicin

tDCS-Induced Memory Reconsolidation Effects and Its Associations With Structural and Functional MRI Substrates in Subjective Cognitive Decline

Previous evidence suggests that transcranial direct current stimulation (tDCS) to the left dorsolateral prefrontal cortex (l-DLPFC) can enhance episodic memory in subjects with subjective cognitive decline (SCD), known to be at risk of dementia. Our main goal was to replicate such findings in an independent sample and elucidate if baseline magnetic resonance imaging (MRI) characteristics predicted putative memory improvement. Thirty-eight participants with SCD (aged: 60-65 years) were randomly assigned to receive active (N = 19) or sham (N = 19) tDCS in a double-blind design. They underwent a verbal learning task with 15 words (DAY-1), and 24 h later (DAY-2) stimulation was applied for 15 min at 1.5 mA targeting the l-DLPFC after offering a contextual reminder. Delayed recall and recognition were measured 1 day after the stimulation session (DAY3), and at 1-month follow-up (DAY-30). Before the experimental session, structural and functional MRI were acquired. We identified a group∗ time interaction in recognition memory, being the active tDCS group able to maintain stable memory performance between DAY-3 and DAY-30. MRI results revealed that individuals with superior tDCSinduced effects on memory reconsolidation exhibited higher left temporal lobe thickness and greater intrinsic FC within the default-mode network. Present findings confirm that tDCS, through the modulation of memory reconsolidation, is capable of enhancing performance in people with self-perceived cognitive complaints. Results suggest that SCD subjects with more preserved structural and functional integrity might benefit from these interventions, promoting maintenance of cognitive function in a population at risk to develop dementia

Brain Connectivity Correlates of Cognitive Dispersion in a Healthy Middle-Aged Population: Influence of Subjective Cognitive Complaints

Objectives: Cognitive dispersion, representing intraindividual fluctuations in cognitive performance, is associated with cognitive decline in advanced age. We sought to elucidate sociodemographic, neuropsychological, and brain connectivity correlates of cognitive dispersion in middle age, and further consider potential influences of the severity of subjective cognitive complaints (SCC). Methods: Five hundred and twenty healthy volunteers from the Barcelona Brain Health Initiative (aged 40-66 years; 49.6% females, 453 with magnetic resonance imaging acquisitions) were included and stratified into high and low SCC groups. Two analysis steps were undertaken: (1) for the whole sample and (2) by groups. Generalized linear models and analysis of covariance were implemented to study associations between cognitive dispersion and performance (episodic memory, speed of processing, and executive function), white matter integrity, and resting-state functional connectivity (rs-FC) of the default mode network (DMN) and dorsal attentional networks (DAN). Results: Across-domain dispersion was negatively related to cognitive performance, rs-FC within the DMN, and between the DMN and the DAN, but not to white matter integrity. The rs-FC values were not explained by cognitive performance. When considering groups, the above findings were significant only for those with high SCC. Discussion: In healthy middle-aged individuals, high cognitive dispersion was related to poorer cognition and DMN dysregulation, being these associations stronger among subjects with high SCC. The present results reinforce the interest in considering dispersion measures within neuropsychological evaluations, as they may be more sensitive to incipient age-related cognitive and functional brain changes than traditional measures of performance

Associations Between Cardiorespiratory Fitness, Cardiovascular Risk, and Cognition Are Mediated by Structural Brain Health in Midlife

Background Evidence in older adults suggests that higher cardiorespiratory fitness and lower cardiovascular risk are associated with greater cognition. However, given that changes in the brain that lead to cognitive decline begin decades before the onset of symptoms, understanding the mechanisms by which modifiable cardiovascular factors are associated with brain health in midlife is critical and can lead to the development of strategies to promote and maintain brain health as we age. Methods and Results In 501 middle‐aged (aged 40–65 years) adult participants of the BBHI (Barcelona Brain Health Initiative), we found differential associations among cardiorespiratory fitness, cardiovascular risk, and cognition and cortical thickness. Higher cardiorespiratory fitness was significantly associated with better visuospatial abilities and frontal loading abstract problem solving (β=3.16, P =0.049) in the older middle‐aged group (aged 55–65 years). In contrast, cardiovascular risk was negatively associated with better visuospatial reasoning and problem‐solving abilities (β=−0.046, P =0.002), flexibility (β=−0.054, P <0.001), processing speed (β=−0.115, P <0.001), and memory (β=−0.120, P <0.001). Cortical thickness in frontal regions mediated the relationship between cardiorespiratory fitness and cognition, whereas cortical thickness in a disperse network spanning multiple cortical regions across both hemispheres mediated the relationship between cardiovascular risk and cognition. Conclusions The relationships between modifiable cardiovascular factors, cardiorespiratory fitness, and cardiovascular risk, and cognition are present in healthy middle‐aged adults. These relationships are also mediated by brain structure highlighting a potential mechanistic pathway through which higher cardiorespiratory fitness and lower cardiovascular risk can positively impact cognitive function in midlife

Brain system segregation and pain catastrophizing in chronic pain progression

Pain processing involves emotional and cognitive factors that can modify pain perception. Increasing evidence suggests that pain catastrophizing (PC) is implicated, through pain-related self-thoughts, in the maladaptive plastic changes related to the maintenance of chronic pain (CP). Functional magnetic resonance imaging (fMRI) studies have shown an association between CP and two main networks: default mode (DMN) and dorsoattentional (DAN). Brain system segregation degree (SyS), an fMRI framework used to quantify the extent to which functional networks are segregated from each other, is associated with cognitive abilities in both healthy individuals and neurological patients. We hypothesized that individuals suffering from CP would show worst health-related status compared to healthy individuals and that, within CP individuals, longitudinal changes in pain experience (pain intensity and affective interference), could be predicted by SyS and PC subdomains (rumination, magnification, and helplessness). To assess the longitudinal progression of CP, two pain surveys were taken before and after an in-person assessment (physical evaluation and fMRI). We first compared the sociodemographic, health-related, and SyS data in the whole sample (no pain and pain groups). Secondly, we ran linear regression and a moderation model only in the pain group, to see the predictive and moderator values of PC and SyS in pain progression. From our sample of 347 individuals (mean age = 53.84, 55.2% women), 133 responded to having CP, and 214 denied having CP. When comparing groups, results showed significant differences in health-related questionnaires, but no differences in SyS. Within the pain group, helplessness (β = 0.325; p = 0.003), higher DMN (β = 0.193; p = 0.037), and lower DAN segregation (β = 0.215; p = 0.014) were strongly associated with a worsening in pain experience over time. Moreover, helplessness moderated the association between DMN segregation and pain experience progression (p = 0.003). Our findings indicate that the efficient functioning of these networks and catastrophizing could be used as predictors of pain progression, bringing new light to the influence of the interplay between psychological aspects and brain networks. Consequently, approaches focusing on these factors could minimize the impact on daily life activities