Communities in DSpace
Select a community to browse its collections.
Recent Submissions
Systematic exploration of psychiatric genetic research publications in Latin America
(2022-10) Garro Núñez, Diana; Picado, María Jesús; Espinoza Campos, Erika Gabriela; Ugalde Araya, Karen Daniela; Chavarría Soley, Gabriela; Macaya Trejos, Gabriel; Raventós Vorst, Henriette
Background: Psychiatric and neurological disorders represent approximately 22% of the total diseases that affect populations in Latin America and the Caribbean. Even though psychiatric disorders have a great impact in terms of mortality, morbidity, and disability across all stages of life, research in mental health has not been a focus for funding agencies, in comparison to other health related research areas. In spite of this situation, several research efforts in different Latin American countries have focused on the genetics of psychiatric disorders. Additionally, some large international research initiatives have included populations of Latin American origin.
The aim of this study is to review the research published with Latin American populations between 2010-2019. We focused mainly on sources of funding, and how this is related to the scope and complexity of the study.
Methods: We performed a systematic literature search from 2010-2019 in the RedalyC and PubMed databases in Spanish, Portuguese, and English. The search terms were constructed with the following format: “Genetic” AND “Psychiatric disorder”, with the phrase “psychiatric disorder” being sequentially replaced by each of ten of the most common psychiatric disorders.
Results: In general, more articles were published within the 2015-2016 period. Additionally, between the 2010-2019 period, depression (20%) and Alzheimer (19%) were the most common disorders found. Most of the Latin American countries' publications were internationally funded, with the exception of Brazil, for which 86% of all publications were locally funded. We found differences between locus specific studies and genome wide studies, regarding sources of funding (local or international) (x^2=9.46; p=0.009). 82% of all whole genome studies were funded by international sources. Over 70% of the studies used SNPs, mostly for association studies, and studies with endophenotypes or traits associated with the disorder. Finally, case/control studies represented the most frequent study design (42%), however an important proportion of the studies were family-based (33%).
Discussion: Our results showed that local funds are generally not large enough for genome-wide studies in Latin America, with the exception of Brazil. As a result, larger studies are often done in collaboration with international partners. We also found that in larger studies the participants are Latin American ancestry subjects living in the USA, not in Latin America. Additionally, our results showed the important role of family-based studies, which have traditionally been a strength in Latin American genetic research because of large family sizes.
In conclusion, limited local funding for research in Latin America has probably contributed to limited sample size, scope, and complexity of psychiatric genetic research studies. Increasing diversity in psychiatric genetics needs to be a future goal in order to improve generalizability and applicability in clinical settings.
P1–206: The search for a successful cognitive aging endophenotype in the offspring of very elderly (90+) nondemented probands in a founder population
(2006-07-01) Edland, Steve; Schnaider Beeri, Michal; Raventos Vorst, Henriette; Valerio Aguilar, Daniel; Corrales Campos, Luis Emilio; Pereira Castro, Mariana; Angelo, Gary; Grossman, Hillel; Bespalova, Irina; Sano, Mary; Silverman, Jeremy M.
Ascertaining families with demonstrable successful cognitive aging might help reveal rare genes associated with good cognitive functioning into very late old age. Given the genetic complexity of this desirable condition, however, validated cognitive endophenotypes (i.e., traits lying midstream between a gene and a genetically complex condition of interest) will be required for open ended gene finding strategies. Delayed recall in particular is a promising candidate endophenotype because it has shown strong heritability in AD proband families and delayed recall impairment has predicted the development of AD.
Objective(s)
To identify cognitive endophenotypes for successful cognitive aging in a founder population.
Methods
Delayed recall, along with other tests of cognitive functions, were assessed in 27 very elderly (age 90+) nondemented (VEND) probands and 47 of their aged 60+ offspring. The families were ascertained from the Central Valley of Costa Rica (CVCR), a founder population. Two sets of CVCR comparison groups were also assessed: 1) Very elderly (aged 90+) demented (VED) probands (n=13) and their age 60+ offspring (n=28); 2) Young (aged 60–70) nondemented elderly (YND; n=15) and their age 60+ siblings (n=17).
Results
VEND offspring, VED offspring, and YND sibling groups did not significantly differ with respect to age, sex, or years of education. Using a random effects model controlling for sex and education, delayed recall was significantly better among VEND offspring than YND siblings(P<0.005) and VED offspring (P<0.05). In addition, there were significant group by education interactions such that fewer years of education was associated with lower delayed recall scores in the YND siblings (P<0.005) and VED offspring (P<0.05), but education had no effect on VEND offspring. Similar albeit nonsignificant relationships were observed with age.
Conclusions
The VEND offspring had higher levels of delayed recall than the VED offspring and YND siblings. In addition, whereas low education was associated with poorer performance in delayed recall in two comparison groups, no such association was present in VEND offspring. These results are consistent with the hypothesis that delayed recall in VEND offspring is a state independent trait and might be a useful endophenotype for successful cognitive aging.
Acute stress and resilient coping: their demographic and psychosocial determinants during Covid-19 pandemic in Costa Rica
(2025-10-22) Reyes Fernández, Benjamín; Jurado Solórzano, Ana María; Raventós Vorst, Henriette; Smith Castro, Vanessa; Rodríguez Arauz, Gloriana
Two cross-sectional studies aimed to describe acute stress and resilient coping responses in samples of adults living in Costa Rica during the COVID-19 pandemic at two time points, and to identify the contribution of sociodemographic and psychosocial variables on these mental health outcomes. Data were collected in 2020 and 2022 via online and telephone surveys, using psychological scales and sociodemographic measures. The telephonic sample (NTP2022 = 1002) was probabilistic (Waksberg method), while online samples (NOL2020 = 2146; NOL2022 = 2157) were non-probabilistic. Descriptive statistics on resilient coping and acute stress from each sample were reported. Loneliness was a stronger determinant of mental health outcomes, compared to sociodemographic variables. Moreover, being older, male, with higher income and feeling less lonely were all associated with better mental health. Educational level was also identified as playing a protective role in mental health, although indirectly, via increased income and decreased loneliness. The sampling strategy and survey administration method should be considered when interpreting descriptive statistics from these studies. Implications derived from these results for future policies and intervention initiatives are discussed.
LiProS: Findable, Accessible, Interoperable, and Reusable Data Simulation Workflow to Predict Accurate Lipophilicity Profiles for Small Molecules
(2025-08-26) Bertsch Aguilar, Esteban; Piedra, Antonio; Acuña Jiménez, Daniel Alonso; Suñer Sánchez, Sebastián; De Souza Pinheiro, Sylvana; Zamora Ramírez, William J.
Lipophilicity is a fundamental physicochemical property widely used to evaluate key parameters in drug design, materials science, and food engineering. It plays a critical role in predicting membrane permeability, absorption, and distribution of compounds. Moreover, lipophilicity is commonly integrated into scoring functions to model biomolecular interactions and serves as an important molecular descriptor in machine learning models for property prediction and compound classification. The election of the appropriate pH-dependent lipophilicity (mathematical equation) model is important to ensure its accuracy. The incorporation of the ion apparent partition coefficient (mathematical equation) into predictions of pH-dependent lipophilicity profiles can be essential for accurately reproducing experimental results. In accordance with the principles for findable, accessible, interoperable, and reusable data to improve data management and sharing, here, we introduce LiProS, a FAIR workflow that is easily accessible through a Google Colab notebook. LiProS assists researchers in efficiently determining the appropriate pH-dependent lipophilicity profile based on the SMILES code of their molecules of interest. In addition, LiProS demonstrated its utility in the analysis of ionizable compounds within the NAPRORE-CR natural products database, enabling the identification of the most appropriate lipophilicity formalism tailored to the physicochemical characteristics of these compounds.
In silico pipeline to identify tumor-specific antigens for cancer immunotherapy using exome sequencing data
(2022-12-08) Morazán Fernández, Diego; Mora Rodríguez, Javier; Molina Mora, José Arturo
Tumor-specific antigens or neoantigens are peptides that are expressed only in cancer cells and not in healthy cells. Some of these molecules can induce an immune response, and therefore, their use in immunotherapeutic strategies based on cancer vaccines has been extensively explored. Studies based on these approaches have been triggered by the current high-throughput DNA sequencing technologies. However, there is no universal nor straightforward bioinformatic protocol to discover neoantigens using DNA sequencing data. Thus, we propose a bioinformatic protocol to detect tumor-specific antigens associated with single nucleotide variants (SNVs) or "mutations" in tumoral tissues. For this purpose, we used publicly available data to build our model, including exome sequencing data from colorectal cancer and healthy cells obtained from a single case, as well as frequent human leukocyte antigen (HLA) class I alleles in a specific population. HLA data from Costa Rican Central Valley population was selected as an example. The strategy included three main steps: (1) pre-processing of sequencing data; (2) variant calling analysis to detect tumor-specific SNVs in comparison with healthy tissue; and (3) prediction and characterization of peptides (protein fragments, the tumor-specific antigens) derived from the variants, in the context of their affinity with frequent alleles of the selected population. In our model data, we found 28 non-silent SNVs, present in 17 genes in chromosome one. The protocol yielded 23 strong binders peptides derived from the SNVs for frequent HLA class I alleles for the Costa Rican population. Although the analyses were performed as an example to implement the pipeline, to our knowledge, this is the first study of an in silico cancer vaccine using DNA sequencing data in the context of the HLA alleles. It is concluded that the standardized protocol was not only able to identify neoantigens in a specific but also provides a complete pipeline for the eventual design of cancer vaccines using the best bioinformatic practices.