Hugo Fitipaldi
A5042428378- Genetic Associations and Epidemiology
- Diabetes Treatment and Management
- Pancreatic function and diabetes
- Liver Disease Diagnosis and Treatment
- Diabetes and associated disorders
- Metabolism, Diabetes, and Cancer
- Bioinformatics and Genomic Networks
- Diabetes, Cardiovascular Risks, and Lipoproteins
- Diabetes Management and Research
- COVID-19 epidemiological studies
- Gestational Diabetes Research and Management
- Bariatric Surgery and Outcomes
- Cardiovascular Disease and Adiposity
- Cardiovascular Function and Risk Factors
- Obesity, Physical Activity, Diet
- Metabolomics and Mass Spectrometry Studies
- Machine Learning in Healthcare
- COVID-19 diagnosis using AI
- GDF15 and Related Biomarkers
- Long-Term Effects of COVID-19
- COVID-19 Clinical Research Studies
- Pregnancy and preeclampsia studies
- Diet, Metabolism, and Disease
- Nuclear Receptors and Signaling
- Folate and B Vitamins Research
Lund University
2018-2024
Skåne University Hospital
2018-2023
Genomics (United Kingdom)
2022
University of Dundee
2022
The detailed characterization of human biology and behaviors is now possible at scale owing to innovations in biomarkers, bioimaging, wearable technologies; “big data” from electronic medical records, health insurance databases, other platforms becoming increasingly accessible; rapidly evolving computational power bioinformatics methods. Collectively, these advances are creating unprecedented opportunities better understand diabetes many complex traits. Identifying hidden structures within...
Background Non-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in individuals with without type 2 diabetes (T2D). Early diagnosis of NAFLD important, as this can help prevent irreversible damage to the and, ultimately, hepatocellular carcinomas. We sought expand etiological understanding develop a diagnostic tool for using machine learning. Methods findings utilized baseline data from IMI DIRECT, multicenter prospective cohort study 3,029...
Abstract Aims/hypothesis Five clusters based on clinical characteristics have been suggested as diabetes subtypes: one autoimmune and four subtypes of type 2 diabetes. In the current study we replicate cross-validate these in three large cohorts using variables readily measured clinic. Methods independent cohorts, total 15,940 individuals were clustered age, BMI, HbA 1c , random or fasting C-peptide, HDL-cholesterol. Clusters cross-validated against original HOMA measures. addition, between...
Abstract Introduction: Since 2005, disease-related human genetic diversity has been intensively characterized using genome-wide association studies (GWAS). Understanding how and by whom this work was performed may yield valuable insights into the generalizability of GWAS discoveries to global populations high-impact genetics research can be equitably sustained in future. Materials Methods: We mined NHGRI-EBI Catalog (2005–2022) for most burdensome non-communicable causes death worldwide....
Abstract Obesity and type 2 diabetes are causally related, yet there is considerable heterogeneity in the consequences of both conditions mechanisms action poorly defined. Here we show a genetic-driven approach defining two obesity profiles that convey highly concordant discordant diabetogenic effects. We annotate then compare association signals for these across clinical molecular phenotypic layers. Key differences identified wide range traits, including cardiovascular mortality, fat...
We identify biomarkers for disease progression in three type 2 diabetes cohorts encompassing 2,973 individuals across molecular classes, metabolites, lipids and proteins. Homocitrulline, isoleucine 2-aminoadipic acid, eight triacylglycerol species, lowered sphingomyelin 42:2;2 levels are predictive of faster towards insulin requirement. Of ~1,300 proteins examined two cohorts, GDF15/MIC-1, IL-18Ra, CRELD1, NogoR, FAS, ENPP7 associated with progression, whilst SMAC/DIABLO, SPOCK1 HEMK2...
Type 2 diabetes is a multifactorial disease with multiple underlying aetiologies. To address this heterogeneity, investigators of previous study clustered people according to five subtypes. The aim the current investigate etiology these clusters by comparing their molecular signatures. In three independent cohorts, in total 15,940 individuals were based on clinical characteristics. subset, genetic (N = 12,828), metabolomic 2,945), lipidomic 2,593), and proteomic 1,170) data obtained plasma....
Abstract The app-based COVID Symptom Study was launched in Sweden April 2020 to contribute real-time COVID-19 surveillance. We enrolled 143,531 study participants (≥18 years) who contributed 10.6 million daily symptom reports between 29, and February 10, 2021. Here, we include data from 19,161 self-reported PCR tests create a symptom-based model estimate the individual probability of symptomatic COVID-19, with an AUC 0.78 (95% CI 0.74–0.83) external dataset. These probabilities are employed...
We evaluate the shared genetic regulation of mRNA molecules, proteins and metabolites derived from whole blood 3029 human donors. find abundant allelic heterogeneity, where multiple variants regulate a particular molecular phenotype, pleiotropy, single variant associates with phenotypes over genomic regions. The highest proportion share is detected between gene expression (66.6%), further median associations across 49 different tissues 78.3% 62.4% plasma expression. represent in networks...
Differences in glucose metabolism among categories of prediabetes have not been systematically investigated. In this longitudinal study, participants (N = 2,111) underwent a 2-h 75-g oral tolerance test (OGTT) at baseline and 48 months. HbA1c was also measured. We classified as having isolated defect (impaired fasting [IFG], impaired [IGT], or indicative [IA1c]), two defects (IFG+IGT, IFG+IA1c, IGT+IA1c), all (IFG+IGT+IA1c). β-Cell function (BCF) insulin sensitivity were assessed from OGTT....