JULIA MARIA PAVAN SOLER

Scopus Publications

From bites to bytes: understanding how and why individual malaria risk varies using artificial intelligence and causal inference
Adèle Helena Ribeiro, Júlia M. P. Soler, Rodrigo M. Corder, Marcelo U. Ferreira, Dominik Heider
Frontiers in Genetics, 2025
With an estimated 263 million cases recorded worldwide in 2023, malaria remains a major global health challenge, particularly in tropical regions with limited healthcare access. Beyond its health impact, malaria disrupts education, economic development, and social equality. While traditional research has focused on biological factors underlying human-mosquito interactions, growing evidence highlights the complex interplay of environmental, behavioral, and socioeconomic factors, alongside mobility and both human and parasite genetics, in shaping transmission dynamics, recurrence patterns, and control effectiveness. This work shows how integrating Artificial Intelligence (AI), Machine Learning (ML), and Causal Inference can advance malaria research by identifying context-specific risk factors, uncovering causal mechanisms, and informing more effective, targeted interventions. Drawing on the Mâncio Lima cohort, a longitudinal, multimodal study of malaria risk in Brazil’s main urban hotspot, and related studies in the Amazon, we highlight how rigorous, data-driven approaches can address the substantial variability in malaria risk across individuals and communities. AI-driven methods facilitate the integration of diverse high-dimensional datasets to uncover intricate patterns and improve individual risk stratification. Federated learning enables collaborative analysis across regions while preserving data privacy. Meanwhile, causal discovery and effect identification tools further strengthen these approaches by distinguishing genuine causal relationships from spurious associations. Together, these approaches offer a principled, scalable, and privacy-preserving framework that enables researchers to move beyond predictive modeling toward actionable causal insights. This shift supports precision public health strategies tailored to vulnerable populations, fostering more equitable and sustainable malaria control and contributing to the reduction of the global malaria burden.
Random Forest Analysis of Out-of-Pocket Health Expenditures Associated with Cardiometabolic Diseases, Lifestyle, Lipid Profile, and Genetic Information in São Paulo, Brazil
Jean Michel R. S. Leite, Lucas A. I. Trindade, Jaqueline L. Pereira, Camila A. de Souza, Júlia M. Pavan Soler, Regina C. Mingroni-Netto, Regina M. Fisberg, Marcelo M. Rogero, Flavia M. Sarti
Healthcare Switzerland, 2024
Background/Objectives: There is a lack of empirical studies of out-of-pocket health expenditures associated with dyslipidemias, which are major cardiovascular risk factors, especially in underrepresented admixed populations. The study investigates associations of health costs with lipid traits, GWAS-derived genetic risk scores (GRSs), and other cardiometabolic risk factors. Methods: Data from the observational cross-sectional 2015 ISA-Nutrition comprised lifestyle, environmental factors, socioeconomic and demographic variables, and biochemical and genetic markers related to the occurrence of cardiometabolic diseases. GWAS-derived genetic risk scores were estimated from SNPs previously associated with lipid traits. There was phenotypic and genetic information available for 490 independent individuals, which was used as inputs for random forests and logistic regression to explain private quantitative and categorical health costs. Results: There were significant correlations between GRSs and their respective lipid phenotypes. The main relevant variables across techniques and outcome variables comprised income per capita, principal components of ancestry, diet quality, global physical activity, inflammatory and lipid markers, and LDL-c GRS and non-HDL-c GRS. The area under the ROC curve (AUC) of quartile-based categorical health expenditure without GRSs was 0.76. GRSs were not significant for this categorical outcome. Conclusions: We present an original contribution to the investigation of determinants of private health expenditures in a highly admixed population, providing insights on associations between genetic and socioeconomic dimensions of health in Brazil. Ancestry information was also among the main factors contributing to health expenses, providing a novel view of the role of genetic ancestry on cardiometabolic risk factors and its potential impact on health costs.
Missense genetic variants in major bitter taste receptors are associated with diet quality and food intake in a highly admixed underrepresented population
Jean Michel R.S. Leite, Adèle Ribeiro, Jaqueline L. Pereira, Camila Alves de Souza, Dominik Heider, Júlia M. Pavan Soler, Regina Célia Mingroni-Netto, Regina M. Fisberg, Marcelo M. Rogero, Flavia M. Sarti
Clinical Nutrition Espen, 2024
Genetic Ancestry and Self-Reported “Skin Color/Race” in the Urban Admixed Population of São Paulo City, Brazil
Jaqueline L. Pereira, Camila A. de Souza, Jennyfer E. M. Neyra, Jean M. R. S. Leite, Andressa Cerqueira, Regina C. Mingroni-Netto, Julia M. P. Soler, Marcelo M. Rogero, Flavia M. Sarti, Regina M. Fisberg
Genes, 2024
Epidemiological studies frequently classify groups based on phenotypes like self-reported skin color/race, which inaccurately represent genetic ancestry and may lead to misclassification, particularly among individuals of multiracial backgrounds. This study aimed to characterize both global and local genome-wide genetic ancestries and to assess their relationship with self-reported skin color/race in an admixed population of Sao Paulo city. We analyzed 226,346 single-nucleotide polymorphisms from 841 individuals participating in the population-based ISA-Nutrition study. Our findings confirmed the admixed nature of the population, demonstrating substantial European, significant Sub-Saharan African, and minor Native American ancestries, irrespective of skin color. A correlation was observed between global genetic ancestry and self-reported color-race, which was more evident in the extreme proportions of African and European ancestries. Individuals with higher African ancestry tended to identify as Black, those with higher European ancestry tended to identify as White, and individuals with higher Native American ancestry were more likely to self-identify as Mixed, a group with diverse ancestral compositions. However, at the individual level, this correlation was notably weak, and no deviations were observed for specific regions throughout the individual’s genome. Our findings emphasize the significance of accurately defining and thoroughly analyzing race and ancestry, especially within admixed populations.
Association of dyslipidemia with single nucleotide polymorphisms of the cholesteryl ester transfer protein gene and cardiovascular disease risk factors in a highly admixed population
Jean Michel R.S. Leite, Jaqueline L. Pereira, Nágila R.T. Damasceno, Júlia M. Pavan Soler, Regina M. Fisberg, Marcelo M. Rogero, Flavia M. Sarti
Clinical Nutrition Espen, 2023
Longitudinal 16S rRNA gut microbiota data of infant triplets show partial susceptibility to host genetics
Ondina Palmeira, Larissa R.B. Matos, Michel S. Naslavsky, Heloisa M.S. Bueno, Júlia P. Soler, João C. Setubal, Mayana Zatz
Iscience, 2022
are particularly susceptible to host genetics. We conclude that infant gut microbiota development is influenced by host genetics, but this effect is subtle and may affect only certain bacterial taxa during a limited time period early in life.
Polymorphisms in Inflammatory Genes Modulate Clinical Complications in Patients With Sickle Cell Disease
Karina Tozatto-Maio, Robert Girot, Indou Deme Ly, Ana Cristina Silva Pinto, Vanderson Rocha, Francisco Fernandes, Ibrahima Diagne, Yahia Benzerara, Carla L. Dinardo, Julia Pavan Soler, Simone Kashima, Itauá Leston Araujo, Chantal Kenzey, Guilherme H. H. Fonseca, Evandra S. Rodrigues, Fernanda Volt, Luciana Jarduli, Annalisa Ruggeri, Christina Mariaselvam, Sandra F. M. Gualandro, Hanadi Rafii, Barbara Cappelli, Felipe Melo Nogueira, Graziana Maria Scigliuolo, Renato Luiz Guerino-Cunha, Kelen Cristina Ribeiro Malmegrim, Belinda P. Simões, Eliane Gluckman, Ryad Tamouza
Frontiers in Immunology, 2020
= 0.049, in patients of same SCD genotype). These results, by uncovering susceptibility to, or protection against SCD complications, might contribute to a better understanding of the inflammatory pathways involved in SCD manifestations and to pave the way for the discovery of biomarkers that predict disease severity, which would improve SCD management.
Learning genetic and environmental graphical models from family data
Adèle H. Ribeiro, Júlia Maria Pavan Soler
Statistics in Medicine, 2020
Many challenging problems in biomedical research rely on understanding how variables are associated with each other and influenced by genetic and environmental factors. Probabilistic graphical models (PGMs) are widely acknowledged as a very natural and formal language to describe relationships among variables and have been extensively used for studying complex diseases and traits. In this work, we propose methods that leverage observational Gaussian family data for learning a decomposition of undirected and directed acyclic PGMs according to the influence of genetic and environmental factors. Many structure learning algorithms are strongly based on a conditional independence test. For independent measurements of normally distributed variables, conditional independence can be tested through standard tests for zero partial correlation. In family data, the assumption of independent measurements does not hold since related individuals are correlated due to mainly genetic factors. Based on univariate polygenic linear mixed models, we propose tests that account for the familial dependence structure and allow us to assess the significance of the partial correlation due to genetic (between-family) factors and due to other factors, denoted here as environmental (within-family) factors, separately. Then, we extend standard structure learning algorithms, including the IC/PC and the really fast causal inference (RFCI) algorithms, to Gaussian family data. The algorithms learn the most likely PGM and its decomposition into two components, one explained by genetic factors and the other by environmental factors. The proposed methods are evaluated by simulation studies and applied to the Genetic Analysis Workshop 13 simulated dataset, which captures significant features of the Framingham Heart Study.
Bayesian diagnostic analysis for quantitative trait loci mapping
Daiane A Zuanetti, Júlia M Pavan Soler, José E Krieger, Luis A Milan
Statistical Methods in Medical Research, 2020
QTL mapping is an important tool for identifying regions in chromosomes which are relevant to explain a response of interest. It is a special case of the regression model where an unknown number of missing (non-observable) covariates is involved leading to a complex variable selection procedure. Although several methods have been proposed to identify QTLs and to estimate parameters in the associated model, minimum attention has been devoted to the estimated model adequacy. In this paper, we present an overview of a few methods for residual and diagnostic analysis in the context of Bayesian regression modeling and adapt them to work with QTL mapping. The motivation of this study is to identify QTLs associated with the blood pressure of F2 rats and check the fitted model adequacy.
Heritability and Sex-Specific Genetic Effects of Self-Reported Physical Activity in a Brazilian Highly Admixed Population
Jean Michel Rocha Sampaio Leite, Júlia Maria Pavan Soler, Andréa Roseli Vançan Russo Horimoto, Rafael O. Alvim, Alexandre C. Pereira
Human Heredity, 2020
Introduction: The engagement in sports or habitual physical activity (PA) has shown an extensive protective role against multiple diseases such as cancer, obesity, and many others. Additionally, PA has also a significant impact on life quality, since it aids with managing stress, preserving cognitive function and memory, and preventing fractures in the elderly. Objective: Considering there has been multiple evidence showing that genetic variation underpins variation of PA-related traits, we aimed to estimate the heritability (h2) of these phenotypes in a sample from the Brazilian population and assess whether males and females differ in relation to those estimates. Methods: 2,027 participants from a highly admixed population from Baependi, MG, Brazil, had information regarding their PA and sedentary behavior (SB) phenotypes collected through a questionnaire (IPAQ-SF). After data cleaning and transformation procedures, we obtained four variables to be evaluated: total PA (TPA MET), walking time, (WK MET), moderate-vigorous PA (MVPA MET), and SB. A model selection procedure was performed using a single-step covariate inclusion approach. We tested for BMI, waist, hip and neck circumferences, smoking, and depression separately, and performed correlation tests among covariates. Linear mixed models, selection procedure, and the variance components approach to estimate h2 were implemented using SOLAR-Eclipse 8.3.1. Results: We obtained estimates of 0.221, 0.109, 0.226, and 0 for TPA MET, WK MET, MVPA MET, and SB, respectively. We found evidence for gene-sex interactions, with males having higher sex-specific heritabilities than females for TPA MET and MVPA MET. In addition, we found higher estimates of the genetic variance component in males than females for most phenotypes. Discussion/Conclusion: The heritability estimates presented in this work show a moderate heritable set of genetic factors affecting PA in a sample from the Brazilian population. The evaluation of the genetic variance component suggests segregating genetic factors in male individuals are more heterogeneous, which can explain why men globally tend to need to practice more intense PA than women to achieve similar health benefits. Hence, these findings have significant implications for the understanding of the genetic architecture of PA and might aid to promote health in the future.
Variance-Preserving Estimation of Intensity Values Obtained From Omics Experiments
Adèle H. Ribeiro, Julia Maria Pavan Soler, Roberto Hirata
Frontiers in Genetics, 2019
Performance of the test of univariate heritability on designs with different family structure
Alex Oliveira RIBEIRO, Daniel Furtado FERREIRA, Júlia Maria Pavan SOLER
Revista Brasileira De Biometria, 2019
Assessing functional status after intensive care unit stay: the Barthel Index and the Katz Index
Leda Tomiko Yamada da Silveira, Janete Maria da Silva, Júlia Maria Pavan Soler, Carolina Yea Ling Sun, Clarice Tanaka, Carolina Fu
International Journal for Quality in Health Care, 2018
Influence of polymorphisms in toll-like receptors (TLRs) on malaria susceptibility in low-endemic area of the Atlantic Forest, São Paulo, Brazil
Lilian O. Guimarães, Francisco Fernandes, Eliana F. Monteiro, Izilda Curado, Marcia M. Holcman, Gerhard Wunderlich, Sidney E. Santos, Júlia M. Soler, Karin Kirchgatter
Acta Tropica, 2018
Impact of CTLA4 genotype and other immune response gene polymorphisms on outcomes after single umbilical cord blood transplantation
Renato Cunha, Marco A. Zago, Sergio Querol, Fernanda Volt, Annalisa Ruggeri, Guillermo Sanz, Fabienne Pouthier, Gesine Kogler, José L. Vicario, Paola Bergamaschi, Riccardo Saccardi, Carmen H. Lamas, Cristina Díaz-de-Heredia, Gerard Michel, Henrique Bittencourt, Marli Tavella, Rodrigo A. Panepucci, Francisco Fernandes, Julia Pavan, Eliane Gluckman, Vanderson Rocha
Blood, 2017
Cohort profile: The Baependi Heart Study - A family-based, highly admixed cohort study in a rural Brazilian town
Kieren J Egan, Malcolm von Schantz, André B Negrão, Hadassa C Santos, Andréa R V R Horimoto, Nubia E Duarte, Guilherme C Gonçalves, Júlia M P Soler, Mariza de Andrade, Geraldo Lorenzi-Filho, Homero Vallada, Tâmara P Taporoski, Mario Pedrazzoli, Ana P Azambuja, Camila M de Oliveira, Rafael O Alvim, José E Krieger, Alexandre C Pereira
BMJ Open, 2016
Bayesian Variable Selection in Multilevel Item Response Theory Models with Application in Genomics
Tiago M. Fragoso, Mariza de Andrade, Alexandre C. Pereira, Guilherme J. M. Rosa, Júlia M. P. Soler
Genetic Epidemiology, 2016
Causal inference and structure learning of genotype-phenotype networks using genetic variation
Adèle H. Ribeiro, Júlia M. P. Soler, Elias Chaibub Neto, André Fujita
Big Data Analytics in Genomics, 2016
Global Individual Ancestry Using Principal Components for Family Data
Mariza de Andrade, Debashree Ray, Alexandre C. Pereira, Júlia P. Soler
Human Heredity, 2015
Polyamines in tomato plants grown during an incidence of tospovirus exposure
Leysimar R. P. Guimarães, Julia M. P. Soler, Giuseppina P. P. Lima, Marcelo A. Pavan
European Journal of Plant Pathology, 2014
Using Item Response Theory to Model Multiple Phenotypes and Their Joint Heritability in Family Data
Tiago M. Fragoso, Suely R. Giolo, Alexandre C. Pereira, Mariza de Andrade, Julia M. P. Soler
Genetic Epidemiology, 2014
Using the theory of added-variable plot for linear mixed models to decompose genetic effects in family data
Nubia E. Duarte, Suely R. Giolo, Alexandre C. Pereira, Mariza de Andrade, Júlia P. Soler
Statistical Applications in Genetics and Molecular Biology, 2014
Genetic analyses of smoking initiation, persistence, quantity, and age-at-onset of regular cigarette use in Brazilian families: The Baependi Heart Study
Andréa RVR Horimoto, Camila M Oliveira, Suely R Giolo, Júlia P Soler, Mariza de Andrade, José E Krieger, Alexandre C Pereira
BMC Medical Genetics, 2012
Brazilian urban population genetic structure reveals a high degree of admixture
Suely R Giolo, Júlia M P Soler, Steven C Greenway, Marcio A A Almeida, Mariza de Andrade, J G Seidman, Christine E Seidman, José E Krieger, Alexandre C Pereira
European Journal of Human Genetics, 2012
Heritability of physical activity traits in Brazilian families: The Baependi Heart Study
Andréa RVR Horimoto, Suely R Giolo, Camila M Oliveira, Rafael O Alvim, Júlia P Soler, Mariza de Andrade, José E Krieger, Alexandre C Pereira
BMC Medical Genetics, 2011
Association of the waist-to-height ratio with cardiovascular risk factors in children and adolescents: The three cities heart study
International Journal of Preventive Medicine, 2010
Evaluating gene by sex and age interactions on cardiovascular risk factors in Brazilian families
Suely R Giolo, Alexandre C Pereira, Mariza de Andrade, José E Krieger, Júlia P Soler
BMC Medical Genetics, 2010
Genetic analysis of age-at-onset for cardiovascular risk factors in a brazilian family study
Suely Ruiz Giolo, Alexandre Costa Pereira, Mariza de Andrade, Camila Maciel de Oliveira, José Eduardo Krieger, Júlia Maria Pavan Soler
Human Heredity, 2009
Congenic strains provide evidence that four mapped loci in chromosomes 2, 4, and 16 influence hypertension in the SHR
Ivy Aneas, Mariliza V. Rodrigues, Bianca A. Pauletti, Gustavo J. J. Silva, Renata Carmona, Leandro Cardoso, Anne E. Kwitek, Howard J. Jacob, Julia M. P. Soler, Jose E. Krieger
Physiological Genomics, 2009
Erbium, chromium:yttrium scandium gallium garnet laser for caries removal: Influence on bonding of a self-etching adhesive system
Arlene Tachibana, Márcia Martins Marques, Julia Maria Pavan Soler, Adriana Bona Matos
Lasers in Medical Science, 2008
Heritability of cardiovascular risk factors in a Brazilian population: Baependi Heart Study
Camila M de Oliveira, Alexandre C Pereira, Mariza de Andrade, Júlia M Soler, José E Krieger
BMC Medical Genetics, 2008
Gene by environment QTL mapping through multiple trait analyses in blood pressure salt-sensitivity: Identification of a novel QTL in rat chromosome 5
Júlia M Pavan Soler, Alexandre C Pereira, César H Tôrres, José E Krieger
BMC Medical Genetics, 2006
Meta-analysis of aspirin for the prevention of preeclampsia: Do the main randomized controlled trials support an association between low-dose aspirin and a reduced risk of developing preeclampsia? [4]
Tiago V. Pereira, Martina Rudnicki, Júlia M.P. Soler, José E. Krieger
Clinics, 2006
Mineralization of stylohyoid ligament complex in patients with temporomandibular disorders and asymptomatic individuals: A comparative study
J. G. C. Luz, L. Rodrigues, I. Chilvarquer, J. M. P. Soler
Journal of Oral Rehabilitation, 2003
Longitudinal familial analysis of blood pressure involving parametric (co)variance functions.
Julia MP Soler, John Blangero
BMC Genetics, 2003
Strategy and model building in the fourth dimension: a null model for genotype x age interaction as a Gaussian stationary stochastic process.
BMC Genetics, 2003
Hemochromatosis gene variants in patients with cardiomyopathy
Alexandre C Pereira, Marco Antonio R Cuoco, Glória F Mota, Fábio F da Silva, Humberto F.G Freitas, Edmar A Bocchi, Júlia Maria P Soler, Alfredo J Mansur, José Eduardo Krieger
American Journal of Cardiology, 2001
Optimal covariance adjustment in growth curve models
Júlia M.P. Soler, Julio M. Singer
Computational Statistics and Data Analysis, 2000
Ovarian follicular dynamics in Nelore breed (Bos indicus) CATTLE
R.A. Figueiredo, C.M. Barros, O.L. Pinheiro, J.M.P. Soler
Theriogenology, 1997