Interaction Effect between Physical Activity and the BDNF Val66Met Polymorphism on Depression in Women from the PISMA-ep Study

This study was partially funded by the Consejeria de Salud, Junta de Andalucia (PI3222009), Consejeria de Innovacion, Proyecto de Excelencia (CTS-2010-6682), the Institute of Health Carlos III (Co-funded by European Regional Development Fund/European Social Fund "A way to make Europe"/"Investing in your future") (projects PI18/00238 and PI18/00467), the Marie Curie Research Grants Scheme (FP7 626235), and by a NARSAD Young Investigator Grant from the Brain & Behavior Research Foundation (22514). Juan Antonio Zarza-Rebollo was supported by the Spanish Ministry of Economy and Competitiveness (BES-2017-082698). Elena Lopez-Isac received financial support from the Spanish Ministry of Science and Innovation Juan de la Cierva Incorporacion Program (grant code IJC2019-040080-I/AEI/10.13039/501100011033). AnaMPerez-Gutierrez was supported by a grant from the Ministry of Economy and Competitiveness and Institute of Health Carlos III (FI19/00228), and Margarita Rivera was supported by the Ministry of Economy and Competitiveness Ramon y Cajal Program (RYC-2014-15774).The relationship between depression and the Val66Met polymorphism at the brain-derived neurotrophic factor gene (BDNF), has been largely studied. It has also been related to physical activity, although the results remain inconclusive. The aim of this study is to investigate the relationship between this polymorphism, depression and physical activity in a thoroughly characterised sample of community-based individuals from the PISMA-ep study. A total of 3123 participants from the PISMAep study were genotyped for the BDNF Val66Met polymorphism, of which 209 had depression. Our results are in line with previous studies reporting a protective effect of physical activity on depression, specifically in light intensity. Interestingly, we report a gene-environment interaction effect in which Met allele carriers of the BDNF Val66Met polymorphism who reported more hours of physical activity showed a decreased prevalence of depression. This effect was observed in the total sample (OR = 0.95, 95%CI = 0.90–0.99, p = 0.027) and was strengthened in women (OR = 0.93, 95%CI = 0.87–0.98, p = 0.019). These results highlight the potential role of physical activity as a promising therapeutic strategy for preventing and adjuvant treatment of depression and suggest molecular and genetic particularities of depression between sexes.Junta de Andalucia PI3222009Consejeria de Innovacion, Proyecto de Excelencia CTS-2010-6682Institute of Health Carlos III (European Regional Development Fund/European Social Fund "A way to make Europe"/"Investing in your future") PI18/00238 PI18/00467Marie Curie Research Grants Scheme FP7 626235NARSAD 22514Spanish Government BES-2017-082698Spanish Ministry of Science and Innovation Juan de la Cierva Incorporacion Program IJC2019-040080-I/AEI/10.13039/501100011033Ministry of Economy and CompetitivenessInstituto de Salud Carlos III FI19/00228Ministry of Economy and Competitiveness Ramon y Cajal Program RYC-2014-1577

Body mass index interacts with a genetic-risk score for depression increasing the risk of the disease in high-susceptibility individuals

This study was funded by the Spanish Ministry of Health, the Institute of Health Carlos III (ISCIII), and the European Regional Development Fund (grants PS09/02272, PS09/02147, PS09/01095, PS09/00849, PS09/00461, and PI12-02755); the Andalusian Council of Health (grant PI-0569-2010); the Spanish Network of Primary Care Research, redIAPP (grant RD06/ 0018); the Aragon group (grant RD06/0018/0020); the Bizkaya group (grant RD06/0018/0018); the Castilla-Leon group (grant RD06/0018/0027); the Mental Health Barcelona Group (grant RD06/0018/0017); the Mental Health, Services and Primary Care Malaga group (grant RD06/0018/0039); and the projects "PI18/00238" and "PI18/00467" funded by the Institute of Health Carlos III (Co-funded by European Regional Development Fund/European Social Fund "A way tomake Europe"/"Investing in your future"). This study was performed as part of a PhD thesis conducted within the Official Doctoral Programme in Biomedicine of the University of Granada, Spain. Augusto Anguita-Ruiz was supported by a Ministry of Economy and Competitiveness and Institute of Health Carlos III fellowship (IFI17/00048). Juan Antonio Zarza-Rebollo received financial support from the Spanish Ministry of Economy and Competitiveness (BES-2017-082698). Ana M. Perez-Gutierrez was supported by a grant from the Ministry of Economy and Competitiveness and Institute of Health Carlos III (FI19/00228). Elena Lopez-Isac received financial support from the Spanish Ministry of Science and Innovation Juan de la Cierva Incorporacion Program (IJC2019040080-I), and Margarita Rivera was supported by the Ministry of Economy and Competitiveness Ramon y Cajal Program (RYC-2014-15774). The authors thank the Institute of Health Carlos III (ISCIII), the European Regional Development Fund (FEDER), the Andalusian Council of Health and Andalusian Health Service (SAS), the Primary Care Prevention and Health Promotion Research Network (redIAPP), the Biomedical Research Institute of Malaga (IBIMA), and the Biomedical Research Centre (CIBM) from the University of Granada for their economic and logistic support. The authors thank all the patients and General Practitioners who participated in the trial.Depression is strongly associated with obesity among other chronic physical diseases. The latest mega- and meta-analysis of genome-wide association studies have identified multiple risk loci robustly associated with depression. In this study, we aimed to investigate whether a genetic-risk score (GRS) combining multiple depression risk single nucleotide polymorphisms (SNPs) might have utility in the prediction of this disorder in individuals with obesity. A total of 30 depression-associated SNPs were included in a GRS to predict the risk of depression in a large case-control sample from the Spanish PredictD-CCRT study, a national multicentre, randomized controlled trial, which included 104 cases of depression and 1546 controls. An unweighted GRS was calculated as a summation of the number of risk alleles for depression and incorporated into several logistic regression models with depression status as the main outcome. Constructed models were trained and evaluated in the whole recruited sample. Non-genetic-risk factors were combined with the GRS in several ways across the five predictive models in order to improve predictive ability. An enrichment functional analysis was finally conducted with the aim of providing a general understanding of the biological pathways mapped by analyzed SNPs. We found that an unweighted GRS based on 30 risk loci was significantly associated with a higher risk of depression. Although the GRS itself explained a small amount of variance of depression, we found a significant improvement in the prediction of depression after including some non-genetic-risk factors into the models. The highest predictive ability for depression was achieved when the model included an interaction term between the GRS and the body mass index (BMI), apart from the inclusion of classical demographic information as marginal terms (AUC = 0.71, 95% CI = [0.65, 0.76]). Functional analyses on the 30 SNPs composing the GRS revealed an over-representation of the mapped genes in signaling pathways involved in processes such as extracellular remodeling, proinflammatory regulatory mechanisms, and circadian rhythm alterations. Although the GRS on its own explained a small amount of variance of depression, a significant novel feature of this study is that including non-genetic-risk factors such as BMI together with a GRS came close to the conventional threshold for clinical utility used in ROC analysis and improves the prediction of depression. In this study, the highest predictive ability was achieved by the model combining the GRS and the BMI under an interaction term. Particularly, BMI was identified as a trigger-like risk factor for depression acting in a concerted way with the GRS component. This is an interesting finding since it suggests the existence of a risk overlap between both diseases, and the need for individual depression genetics-risk evaluation in subjects with obesity. This research has therefore potential clinical implications and set the basis for future research directions in exploring the link between depression and obesityassociated disorders. While it is likely that future genome-wide studies with large samples will detect novel genetic variants associated with depression, it seems clear that a combination of genetics and non-genetic information (such is the case of obesity status and other depression comorbidities) will still be needed for the optimization prediction of depression in high-susceptibility individuals.Instituto de Salud Carlos III Spanish Government Institute of Health Carlos III (ISCIII) European Commission PS09/02272 PS09/02147 PS09/01095 PS09/00849 PS09/00461 PI12-02755Andalusian Council of Health PI-0569-2010Spanish Network of Primary Care Research, redIAPP RD06/ 0018Gobierno de Aragon RD06/0018/0020Bizkaya group RD06/0018/0018Castilla-Leon group RD06/0018/0027Mental Health Barcelona Group RD06/0018/0017Mental Health, Services and Primary Care Malaga group RD06/0018/0039Instituto de Salud Carlos III PI18/00238 PI18/00467 FI19/00228European Regional Development Fund/European Social Fund "A way tomake Europe"/"Investing in your future"Ministry of Economy and CompetitivenessInstitute of Health Carlos III fellowship IFI17/00048Spanish Government BES-2017-082698Spanish Ministry of Science and Innovation Juan de la Cierva Incorporacion Program IJC2019040080-IMinistry of Economy and Competitiveness Ramon y Cajal Program RYC-2014-15774Andalusian Council of HealthAndalusian Health Service (SAS)Primary Care Prevention and Health Promotion Research Network (redIAPP)Biomedical Research Institute of Malaga (IBIMA)Biomedical Research Centre (CIBM) from the University of GranadaEuropean Commissio

Body mass index interacts with a genetic-risk score for depression increasing the risk of the disease in high-susceptibility individuals

Depression is strongly associated with obesity among other chronic physical diseases. The latest mega- and meta-analysis of genome-wide association studies have identified multiple risk loci robustly associated with depression. In this study, we aimed to investigate whether a genetic-risk score (GRS) combining multiple depression risk single nucleotide polymorphisms (SNPs) might have utility in the prediction of this disorder in individuals with obesity. A total of 30 depression-associated SNPs were included in a GRS to predict the risk of depression in a large case-control sample from the Spanish PredictD-CCRT study, a national multicentre, randomized controlled trial, which included 104 cases of depression and 1546 controls. An unweighted GRS was calculated as a summation of the number of risk alleles for depression and incorporated into several logistic regression models with depression status as the main outcome. Constructed models were trained and evaluated in the whole recruited sample. Non-genetic-risk factors were combined with the GRS in several ways across the five predictive models in order to improve predictive ability. An enrichment functional analysis was finally conducted with the aim of providing a general understanding of the biological pathways mapped by analyzed SNPs. We found that an unweighted GRS based on 30 risk loci was significantly associated with a higher risk of depression. Although the GRS itself explained a small amount of variance of depression, we found a significant improvement in the prediction of depression after including some non-genetic-risk factors into the models. The highest predictive ability for depression was achieved when the model included an interaction term between the GRS and the body mass index (BMI), apart from the inclusion of classical demographic information as marginal terms (AUC = 0.71, 95% CI = [0.65, 0.76]). Functional analyses on the 30 SNPs composing the GRS revealed an over-representation of the mapped genes in signaling pathways involved in processes such as extracellular remodeling, proinflammatory regulatory mechanisms, and circadian rhythm alterations. Although the GRS on its own explained a small amount of variance of depression, a significant novel feature of this study is that including non-genetic-risk factors such as BMI together with a GRS came close to the conventional threshold for clinical utility used in ROC analysis and improves the prediction of depression. In this study, the highest predictive ability was achieved by the model combining the GRS and the BMI under an interaction term. Particularly, BMI was identified as a trigger-like risk factor for depression acting in a concerted way with the GRS component. This is an interesting finding since it suggests the existence of a risk overlap between both diseases, and the need for individual depression genetics-risk evaluation in subjects with obesity. This research has therefore potential clinical implications and set the basis for future research directions in exploring the link between depression and obesity-associated disorders. While it is likely that future genome-wide studies with large samples will detect novel genetic variants associated with depression, it seems clear that a combination of genetics and non-genetic information (such is the case of obesity status and other depression comorbidities) will still be needed for the optimization prediction of depression in high-susceptibility individuals

Genome-wide association study (gwas) for depression in an andalusian epidemiological sample. Relationship between body mass index, physical activity and depression

Depression is a highly prevalent mental disorder with devastating consequences in the general population, posing a public health concern worldwide. The increased mortality associated with depression is largely related to its frequent comorbidity with physical illnesses and other mental disorders, aggravating patients' prognosis and complicating their treatment. Furthermore, depression is a genetically complex disorder, with multiple common genetic variants involved in its aetiology, and it is the aggregation of risk alleles that confers a certain genetic predisposition. The general aim of this Doctoral Thesis is to investigate the genetic differences between individuals with depression and controls in an adult epidemiological sample, representative of the general Andalusian population (the PISMA-ep study), and to identify potential interactions between the genetic background of an individual and environmental factors related to physical health. Chapter I aims to conduct a genome-wide association study (GWAS) for depression in an subsample of an epidemiological cohort representative of the general adult population of Andalusia from the PISMA-ep study. Although no variable was found to reach statistical significance at the genome-wide level, 9 genetic risk variants were found in the "grey zone" and were analysed. The construction of a polygenic risk score (PRS) allowed us to establish an association between depression prevalence in the PISMA-ep subsample and a weighted set of genetic variants that were identified in the largest depression GWAS meta-analysis to date. In Chapters II and III, the focus shifts to the relationship between depression and physical health, focusing on the role of body mass index (BMI) and physical activity, respectively. Chapter II aims to investigate the relationship between depression and BMI as an indicator of physical health, because of its relationship with obesity. To this end, firstly, a systematic review of the most studied polymorphism of the FTO gene (rs9939609, classically associated with an increase in BMI) was carried out to elucidate the potential relationship between this genetic variant, depression and BMI, although we highlighted the need for more methodologically homogeneous studies to obtain conclusive results. Subsequently, a new unweighted genetic risk score (GRS) was constructed from the sum of risk alleles from variants of 30 candidate genes for depression in a Spanish epidemiological cohort (PredictD-CCRT). In addition to being associated with depression, we found an improvement in the predictive ability of the model when nongenetic risk factors were included, and in particular an interaction between BMI and the GRS was observed. Chapter III aims to explore the relationship between physical activity and depression. To begin, we conducted a systematic review of BDNF and its relationship with depression and physical activity, both of its most studied polymorphism (rs6265, Val66Met) and of the levels of the protein. Despite the need for consensus that was highlighted, the results suggested a transient increase in the protein as an acute effect of physical activity, as well as a greater antidepressant effect due to exercise reported in carriers of the risk allele (Met) of the variant studied. In the following study, we sought to analyse whether this BDNF polymorphism was related to depression and physical activity in the PISMA-ep study. In both the total sample and in women, we observed the effect described in the systematic review, i.e. a decrease in the prevalence of depression in people carrying the risk allele, which became more pronounced as the reported weekly hours of physical activity increased. Chapter IV integrates the insights from the previous chapters by constructing a PRS for depression in a phenotypically characterised PISMA-ep subsample comprising BMI and physical activity information. Using the summary statistics of the largest GWAS meta-analysis to date, it was observed that a higher polygenic risk was associated with a higher prevalence of depression in the subsample analysed. Furthermore, the addition of non-genetic variables, such as not being physically active or higher BMI, improved the predictive ability of the model and its association with the prevalence of depression. The results described in this Doctoral Thesis contribute to the knowledge about the genetic architecture of depression, by means of a GWAS study and PRS constructions. Furthermore, they provide evidence that, for a better prediction of depression risk, incorporating variables related to physical health such as BMI and physical exercise would be particularly valuableLa depresión es un trastorno mental altamente prevalente, con consecuencias devastadoras en la población general, suponiendo un desafío en materia de salud pública a nivel mundial. El aumento de mortalidad asociado a la depresión está en gran parte relacionado con su frecuente comorbilidad con enfermedades físicas y otros trastornos mentales, agravando el pronóstico de los pacientes y complicando su tratamiento. Por otro lado, la depresión es un trastorno genéticamente complejo, con múltiples variantes genéticas comunes involucradas en su etiología, y es la agregación de los alelos de riesgo la que confiere una cierta predisposición genética. El objetivo general de esta tesis es investigar las diferencias genéticas entre casos con depresión y controles en una muestra epidemiológica adulta, representativa de la población general andaluza, e identificar potenciales interacciones entre la variabilidad genética de un individuo y condicionantes de su entorno relativos a la salud física. En el Capítulo I se tiene como objetivo llevar a cabo un estudio de asociación del genoma completo (GWAS, genome wide association study) para depresión en una submuestra proveniente del estudio epidemiológico PISMA-ep, representativo de la población general adulta andaluza. Pese a no encontrar ninguna variable que alcanzase la significancia estadística a nivel de genoma completo, 9 variantes genéticas de riesgo se encontraron en la “zona gris” y fueron analizadas. La construcción de una puntuación de riesgo poligénico (PRS, polygenic risk score) nos permitió establecer una asociación entre prevalencia de depresión en la submuestra de la cohorte PISMA-ep y un conjunto ponderado de variantes genéticas que fueron identificadas en el metaanálisis de GWAS más extenso realizado en depresión hasta la fecha. En los Capítulos II y III, el foco se traslada a la relación entre la depresión y la salud física, centrándonos en el papel del índice de masa corporal (IMC) y de la actividad física, respectivamente. En el Capítulo II se plantea el objetivo de investigar la relación entre depresión e IMC como indicador de la salud física, por su relación con la obesidad. Para ello, en primer lugar, se llevó a cabo una revisión sistemática sobre el polimorfismo más estudiado del gen FTO, rs9939609, clásicamente asociado a un incremento en el IMC, para elucidar la posible relación existente entre esta variante, depresión e IMC, aunque se destacó la necesidad de estudios metodológicamente más homogéneos para obtener resultados concluyentes. Seguidamente, se construyó una nueva puntuación de riesgo genético no ponderado a partir de la suma de 30 alelos de riesgo de variantes genéticas en genes candidatos para depresión, en una cohorte epidemiológica española (PredictD-CCRT). Además de asociarse a depresión, encontramos una mejora en la habilidad predictiva del modelo cuando se incluían factores de riesgo no genéticos, y en particular se observó una interacción entre el IMC y la puntuación de riesgo genético. El Capítulo III plantea como objetivo profundizar en la relación entre actividad física y depresión. Se comenzó con una revisión sistemática sobre BDNF y su relación con depresión y actividad física tanto de su polimorfismo más estudiado (rs6265, Val66Met) como de los niveles de la proteína. Pese a la necesidad de consenso que se observó, los resultados sugirieron un aumento transitorio de la proteína como efecto agudo de la actividad física, así como un mayor efecto antidepresivo a causa del ejercicio reportado en portadores del alelo de riesgo (Met) de la variante estudiada. En el siguiente estudio, tratamos de analizar si este polimorfismo se relacionaba con depresión y actividad física en la cohorte del estudio PISMA-ep. Tanto en la muestra completa como en mujeres, observamos el efecto descrito en la revisión sistemática, es decir, una disminución de la prevalencia de depresión en las personas portadoras del alelo de riesgo, que se acrecentaba conforme aumentaban las horas semanales reportadas de actividad física. El Capítulo IV integra las perspectivas de los capítulos previos, construyendo un PRS para depresión en una submuestra del estudio PISMA-ep caracterizada a nivel fenotípico, conteniendo información de IMC y actividad física. Empleando los resultados del metaanálisis de GWAS más extenso hasta la fecha, se observó que un mayor riesgo poligénico estaba asociado con una mayor prevalencia de depresión en la submuestra analizada. Además, la adición de variables no genéticas, como el no practicar actividad física o un mayor IMC, mejoraron la habilidad predictiva del modelo y su asociación con la prevalencia de depresión. Los resultados descritos en esta Tesis Doctoral contribuyen a ampliar los conocimientos acerca de la arquitectura genética de la depresión, por medio de un estudio GWAS y construcciones de PRS. Además, aportan evidencia de que, para una mejor predicción del riesgo de depresión, es importante incorporar variables relativas a la salud física tales como el IMC y la práctica de ejercicio físico.Tesis Univ. Granada.Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016, con referencia BES-2017- 082698Ministerio de Economía, Industria y Competitividad (MINECO)Agencia Estatal de Investigació

Delving into the relationship between regular physical exercise and cardiac interoception in two cross-sectional studies.

Cardiac interoception, the ability to sense and process cardiac afferent signals, has been shown to improve after a single session of acute physical exercise. However, it remains unclear whether repetitive engagement in physical exercise over time leads to long-term changes in cardiac interoceptive accuracy. It is also unknown whether those changes affect the neural activity associated with the processing of afferent cardiac signals, assessed by the heart-evoked potential (HEP). In this study, we aimed to investigate this hypothesis through two cross-sectional studies, categorizing participants as active or inactive based on physical fitness (Study I; N = 45) or self-reported physical activity levels (Study II; N = 60). Interoception was assessed at rest using the HEP (Studies I and II), the Heartbeat Counting task (Study II), and the Rubber Hand Illusion (RHI) (Study II). Study I showed strong evidence of better cardiovascular fitness in the active group than in the inactive group as well as robust between-group differences in electrocardiogram (ECG) recordings. Study 2 replicated the clear differences in ECG as a function of regular physical activity. Those results were expected due to clear differences in physical activity habits. In contrast, our analysis revealed no robust differences between groups across cardiac interoception tasks and the RHI, although the direct relevance of these measures to interoception remains under investigation. In sum, our results do not provide convincing evidence to support a strong version of the notion that regular physical exercise is associated with an enhanced in cardiac interoception

Neotropical ornithology: Reckoning with historical assumptions, removing systemic barriers, and reimagining the future

A major barrier to advancing ornithology is the systemic exclusion of professionals from the Global South. A recent special feature, Advances in Neotropical Ornithology, and a shortfalls analysis therein, unintentionally followed a long-standing pattern of highlighting individuals, knowledge, and views from the Global North, while largely omitting the perspectives of people based within the Neotropics. Here, we review current strengths and opportunities in the practice of Neotropical ornithology. Further, we discuss problems with assessing the state of Neotropical ornithology through a northern lens, including discovery narratives, incomplete (and biased) understanding of history and advances, and the promotion of agendas that, while currently popular in the north, may not fit the needs and realities of Neotropical research. We argue that future advances in Neotropical ornithology will critically depend on identifying and addressing the systemic barriers that hold back ornithologists who live and work in the Neotropics: unreliable and limited funding, exclusion from international research leadership, restricted dissemination of knowledge (e.g., through language hegemony and citation bias), and logistical barriers. Moving forward, we must examine and acknowledge the colonial roots of our discipline, and explicitly promote anti-colonial agendas for research, training, and conservation. We invite our colleagues within and beyond the Neotropics to join us in creating new models of governance that establish research priorities with vigorous participation of ornithologists and communities within the Neotropical region. To include a diversity of perspectives, we must systemically address discrimination and bias rooted in the socioeconomic class system, anti-Blackness, anti-Brownness, anti-Indigeneity, misogyny, homophobia, tokenism, and ableism. Instead of seeking individual excellence and rewarding top-down leadership, institutions in the North and South can promote collective leadership. In adopting these approaches, we, ornithologists, will join a community of researchers across academia building new paradigms that can reconcile our relationships and transform science. Spanish and Portuguese translations are available in the Supplementary Material.• Research conducted by ornithologists living and working in Latin America and the Caribbean has been historically and systemically excluded from global scientific paradigms, ultimately holding back ornithology as a discipline.• To avoid replicating systems of exclusion in ornithology, authors, editors, reviewers, journals, scientific societies, and research institutions need to interrupt long-held assumptions, improve research practices, and change policies around funding and publication.• To advance Neotropical ornithology and conserve birds across the Americas, institutions should invest directly in basic field biology research, reward collective leadership, and strengthen funding and professional development opportunities for people affected by current research policies.Peer reviewe