Repositório Científico do Instituto Nacional de Saúde
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Obesity rise plateaus in developed nations and accelerates in developing nations
Publication . NCD Risk Factor Collaboration Consortium
Global reporting of obesity is commonly based on comparisons over multiple decades and lacks a granular and systematic analysis of its dynamics. We used 4,050 population-based studies with measured height and weight data on 232 million participants to assess the worldwide dynamics of obesity from 1980 to 2024. The rise in obesity decelerated in school-aged children and adolescents throughout the 1990s in many high-income countries, and subsequently plateaued in most at age-standardized prevalences spanning 20 percentage points, from 3-4% for girls in Japan, Denmark and France to 23% for boys in the USA. There were indications of a small decline in obesity in children and adolescents in some high-income western countries (for example, Italy, Portugal and France) since the 2000s. Similar trends were seen in some countries in Central and Eastern Europe. In adults, the rise in obesity slowed down in high-income western countries about a decade after children, followed by a plateau or possibly a small reversal of the rise in some countries (for example, Spain). In most low-income and middle-income countries, the annual absolute change in prevalence has remained stable or increased over time, even though prevalence has surpassed that of high-income countries. These highly varied dynamics suggest that the social, economic and technological trends that influence the availability, affordability and use of different foods may have helped control the rise in obesity in high-income countries, but require policy interventions in low-income and middle-income countries.
Attainment of global diabetes targets in 2021: a pooled analysis of individual-level data from national surveys in 100 low-income, middle-income, and high-income countries
Publication . Global Health and Population Project on Access to Care for Cardiometabolic Diseases Collaborators
Background: WHO launched the Global Diabetes Compact in 2021 to improve worldwide diabetes outcomes by scaling up access to comprehensive, affordable, and high-quality care. This initiative established population diabetes metrics and targets for countries to attain by 2030, namely, 80% of all people with diabetes are diagnosed; and, among people with diagnosed diabetes, 80% have good glycaemic control (HbA1c <8·0%), 80% have good blood pressure control (<140/90 mm Hg), and 60% of people older than 40 years use statins. We aimed to estimate attainment of global diabetes targets worldwide and across country and individual characteristics in 2021.
Methods: We analysed pooled, individual participant data from nationally representative household health surveys done in 100 low-income, middle-income, and high-income countries between 2010 and 2023. The sample included non-pregnant adults aged 30-69 years. Diabetes was defined as use of glucose-lowering medications or biochemical evidence of diabetes (fasting plasma glucose ≥7·0 mmol/L or HbA1c ≥6·5% [48 mmol/mol]). The primary outcomes were the proportion of people attaining each diabetes metric. We analysed data using hierarchical Bayesian logistic regression models with the survey year set to 2021. We estimated the age-standardised proportion attaining each metric across the pooled dataset, by country-level characteristics such as World Bank income group, by country, and by individual-level characteristics including age, sex, educational attainment, and BMI.
Findings: In 2021, across the pooled dataset, the age-standardised proportion of people with diabetes who had been diagnosed was 63·2% (95% CI 61·8-64·6). Among those diagnosed, 63·2% (62·1-64·4) achieved glycaemic control (HbA1c <8·0%), 70·8% (69·8-71·9) achieved blood pressure control (<140/90 mm Hg), and 31·8% (30·4-33·2) were using statins. Of the 100 included countries, eight met the target for diabetes diagnosis, seven met the target for glycaemic control, 15 met the target for blood pressure control, and eight met the target for statin use. By country income group, the age-standardised proportion of people with diabetes who had been diagnosed ranged from 35·3% (33·5-37·1) in low-income countries to 69·9% (68·3-71·5) in high-income countries. Among those with diagnosed diabetes, glycaemic control ranged from 56·0% (54·2-57·8) in lower-middle-income countries to 73·7% (72·7-74·6) in high-income countries; blood pressure control ranged from 58·3% (57·3-59·4) in lower-middle-income countries to 82·4% (81·4-83·4) in high-income countries; and statin use ranged from 9·7% (8·0-11·4) in low-income countries to 58·7% (57·4-59·9) in high-income countries. Across individual-level characteristics, patterns of inequities were observed in the attainment of each metric.
Interpretation: There are pronounced inequities at multiple levels in the attainment of global diabetes metrics. Substantial progress is needed to reduce inequities and to achieve the 2030 targets.
Evaluation of FASP for Mass Spectrometry-Based Untargeted Metabolomics analysis of urine samples
Publication . Mousa, Muath Khairi; Carvalho, Luis B.; Giddey, Alexander D.; Figueiredo, André; Al-Hroub, Hamza; Semreen, Mohammad H.; Uddin, Mohammed; Santos, Hugo M.; Soares, Nelson C.
Filter-Aided Sample Preparation (FASP) is a well-established method in proteomics, yet its potential for the parallel recovery of metabolites remains largely unexplored. Herein, we evaluate the performance of FASP as a straightforward workflow for the simultaneous isolation of protein and corresponding metabolite fractions from a single urine sample. The FASP-based LC-MS/MS approach for both proteomics and metabolomics analysis identified 3,163 nonredundant peptides corresponding to 957 unique protein groups. The metabolomic profile comparison of three urine fractions, specifically FASP-concentrated, FASP flow-through, and raw samples, resulted in the identification of 176 common metabolites. Next, as a proof-of-concept, the FASP protocol was applied to compare the metabolomic profiles of clinical urine samples from healthy individuals (n = 13) and patients with Ta bladder cancer (n = 12). The metabolomic modulation was consistent with previously reported findings, highlighting perturbations in phenylacetate, purine, and tryptophan metabolism, as reflected by changes in metabolites such as adenosine monophosphate (AMP), phenylacetic acid, glutamine, cytosine, and l-tryptophan. FASP protocol can be effectively adapted for the concurrent profiling of both proteomic and metabolomic fractions from urine samples. Thus, FASP-based workflow represents a viable alternative for single-step sample preparation, facilitating subsequent quantitative multiomics data integration.
Artificial Intelligence and multiomics beyond PSA screening in African and Middle Eastern prostate cancer patients
Publication . Al-Shahrabi, Rula; Alkhnbashi, Omer S.; Almarri, Rauda S.B.; Ahmad, Sarfraz; Soares, Nelson C.; Al Shareef, Zainab
Prostate cancer (PCa) remains a major global health burden, with incidence rising as populations age. The molecular, histological, and patient-specific heterogeneity of PCa underscores the urgent need for advanced strategies to improve detection and risk stratification. This review highlights how multiomics integration, including transcriptomics, DNA methylation, proteomics, and metabolomics, combined with artificial intelligence (AI), can validate biological mechanisms across molecular layers, thereby enhancing diagnostic reliability and biological relevance. While prostate-specific antigen (PSA) testing has significantly shaped PCa epidemiology, its limited specificity and sensitivity have led to widespread overdiagnosis and overtreatment, particularly of indolent tumors. These limitations are especially pronounced in underrepresented populations, notably men of African descent and those in the Middle East and North Africa (MENA) region, where PSA-based screening demonstrates reduced effectiveness. Despite advances in biomarker discovery, current datasets lack sufficient ethnic and regional diversity, raising concerns about the clinical validity and equity of AI-driven models. We argue that equitable precision oncology requires not only technological innovation but also the development of inclusive, demographically representative datasets. This review offers a forward-looking perspective on advancing PCa screening and stratification beyond PSA, with a particular emphasis on addressing the unmet clinical needs of African and Middle Eastern patients.
ARPE-19-A Stable Cell Line Expressing a Variant of Unknown Significance in the NPC1 Gene
Publication . Monteiro, Beatriz; Peixoto, Maria Inês; Ortigoza-Escobar, Juan Darío; Alves, Mariana; Sandiares, Ana Catarina; Gonçalves, Mariana; Vaz Moreira, Luciana; Coutinho, Maria Francisca; Matos, Liliana; Alves, Sandra; Encarnação, Marisa
Background: Niemann-Pick type C is a lysosomal storage disorder that results from pathogenic variants in the NPC1 gene or in some cases from NPC2 pathogenic alterations. The disease presents a remarkable clinical variability that in some cases resembles common diseases, often resulting in a diagnostic odyssey or at least delaying proper diagnosis. In addition, the NPC1 gene is highly polymorphic, and consequently, when missense variants are identified after gene sequencing, accurate classification of their pathogenicity is essential to ensure appropriate access to available therapies and to provide reliable genetic counseling.
Objectives: To get insights into the pathogenicity of a novel variant in NPC1, p.Cys800Ser, we created stable cell lines expressing this variant, in parallel with cell lines expressing the NPC1 wild-type and NPC1 pathogenic variants.
Methods: We leveraged an isogenic cell line in which the NPC1 gene was knocked down and subsequently infected it with retroviruses carrying NPC1-WT and NPC1 variants C-terminally fused with an mNeonGreen tag. Three different NPC1 variants were included in this study: two known pathogenic variants, p.Ala1035Val and p.Pro1007Ala, and the novel p.Cys800Ser, whose significance was unknown.
Results: We observed in the stable cell line expressing NPC1 p.Cys800Ser that the mutated NPC1 protein is transported to the lysosome similarly to the p.Pro1007Ala variant and affects lysosomal distribution.
Conclusions: Using this approach, we could analyze the pathogenicity of each variant separately and these cell lines could be used for personalized medicine-based approaches and multi-omic studies.