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The lack of sex-specific cardiovascular disease criteria contributes to the underdiagnosis of women compared to that of men. For more than half a century, the Framingham Risk Score has been the gold standard to estimate an individual's risk of developing cardiovascular disease based on the age, sex, cholesterol levels, blood pressure, diabetes status, and the smoking status. Now, machine learning can offer a much more nuanced insight into predicting the risk of cardiovascular diseases. The UK Biobank is a large database that includes traditional risk factors and tests related to the cardiovascular system: magnetic resonance imaging, pulse wave analysis, electrocardiograms, and carotid ultrasounds. Here, we leverage 20,542 datasets from the UK Biobank to build more accurate cardiovascular risk models than the Framingham Risk Score and quantify the underdiagnosis of women compared to that of men. Strikingly, for a first-degree atrioventricular block and dilated cardiomyopathy, two conditions with non-sex-specific diagnostic criteria, our study shows that women are under-diagnosed 2× and 1.4× more than men. Similarly, our results demonstrate the need for sex-specific criteria in essential primary hypertension and hypertrophic cardiomyopathy. Our feature importance analysis reveals that out of the top 10 features across three sexes and four disease categories, traditional Framingham factors made up between 40% and 50%; electrocardiogram, 30%-33%; pulse wave analysis, 13%-23%; and magnetic resonance imaging and carotid ultrasound, 0%-10%. Improving the Framingham Risk Score by leveraging big data and machine learning allows us to incorporate a wider range of biomedical data and prediction features, enhance personalization and accuracy, and continuously integrate new data and knowledge, with the ultimate goal to improve accurate prediction, early detection, and early intervention in cardiovascular disease management. Our analysis pipeline and trained classifiers are freely available at https://github.com/LivingMatterLab/CardiovascularDiseaseClassification.
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BACKGROUND: Fruit consumption has been associated with a lower cardiovascular disease (CVD) risk but the underlying mechanisms are unclear. We investigated the cross-sectional and prospective associations of fruit consumption with markers of adiposity, blood pressure, lipids, low-grade inflammation, glycaemia, and oxidative stress. METHODS: The main analyses included 365 534 middle-aged adults from the UK Biobank at baseline, of whom 11 510, and 38 988 were included in the first and second follow-up respectively, free from CVD and cancer at baseline. Fruit consumption frequency at baseline was assessed using a questionnaire. We assessed the cross-sectional and prospective associations of fruit with adiposity (body mass index, waist circumference and %body fat), systolic and diastolic blood pressure, lipids (low-density and high-density lipoproteins, triglycerides and apolipoprotein B), glycaemia (haemoglobin A1c), low-grade inflammation (C-reactive protein) and oxidative stress (gamma-glutamyl-transferase) using linear regression models adjusted for socioeconomic and lifestyle factors. Analyses were repeated in a subset with two to five complete 24-h dietary assessments (n = 26 596) allowing for adjustment for total energy intake. RESULTS: Fruit consumption at baseline generally showed weak inverse associations with adiposity and biomarkers at baseline. Most of these relationships did not persist through follow-up, except for inverse associations with diastolic blood pressure, C-reactive protein, gamma-glutamyl transferase and adiposity. However, for most mechanisms, mean levels varied by less than 0.1 standard deviations (SD) between high and low fruit consumption (> 3 vs < 1 servings/day) in further adjusted models (while the difference was < 0.2 SD for all of them). For example, waist circumference and diastolic blood pressure were 1 cm and 1 mmHg lower in high compared to low fruit intake at the first follow-up (95% confidence interval: -1.8, -0.1 and -1.8, -0.3, respectively). Analyses in the 24-h dietary assessment subset showed overall similar associations. CONCLUSIONS: We observed very small differences in adiposity and cardiometabolic biomarkers between those who reported high fruit consumption vs low, most of which did not persist over follow-up. Future studies on other mechanisms and detailed assessment of confounding might further elucidate the relevance of fruit to cardiovascular disease.
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Adiposidade , Biomarcadores , Frutas , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Biomarcadores/sangue , Pressão Sanguínea/fisiologia , Fatores de Risco Cardiometabólico , Doenças Cardiovasculares/epidemiologia , Estudos Transversais , Dieta/estatística & dados numéricos , Lipídeos/sangue , Estresse Oxidativo/fisiologia , Estudos Prospectivos , Biobanco do Reino Unido/estatística & dados numéricos , Reino Unido/epidemiologiaRESUMO
BACKGROUND: Parkinson's disease (PD) is a neurodegenerative influenced by various clinical factors. The potential relationship between renal function and the risk of PD remains poorly understood. This study aims to explore the association between kidney function and the risk of developing PD. METHODS: A population-based cohort study was conducted using data from 400,571 UK Biobank participants. Renal function was assessed using the estimated glomerular filtration rate (eGFR), calculated from serum creatinine and cystatin C levels. The association between eGFR levels and PD risk was evaluated using univariate and multivariate Cox regression analyses, Restricted Cubic Spline (RCS) analysis, and Kaplan-Meier analysis. Additionally, a clinical prediction model was developed and its diagnostic accuracy was evaluated using ROC analysis. A heatmap was also constructed to examine the relationship between clinical factors and gray matter volume in various brain regions. RESULTS: Over a median observation period of 13.8 years, 2740 PD events were recorded. Cox regression and Kaplan-Meier analyses revealed a significant association between decreased eGFR and increased PD risk, particularly in participants with eGFR < 30 ml/min/1.73 m2. This association was confirmed across three adjusted models. RCS analysis demonstrated a nonlinear relationship between decreasing eGFR and increasing PD risk. Furthermore, changes in eGFR were correlated with alterations in subcortical gray matter volume in regions such as the frontal cortex, striatum, and cerebellum. The clinical prediction model showed high diagnostic accuracy with AUC values of 0.776, 0.780, and 0.824 for 4-, 8-, and 16-year predictions, respectively. CONCLUSION: Renal insufficiency is significantly associated with an increased risk of PD, highlighting the importance of maintaining good kidney function as a potential preventive measure against PD.
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Taxa de Filtração Glomerular , Doença de Parkinson , Adulto , Idoso , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Cistatina C/sangue , Taxa de Filtração Glomerular/fisiologia , Doença de Parkinson/epidemiologia , Doença de Parkinson/fisiopatologia , Estudos Prospectivos , Fatores de Risco , Biobanco do Reino Unido , Reino Unido/epidemiologiaRESUMO
BACKGROUND: Proteomics and metabolomics offer substantial potential for advancing kidney transplant research by providing versatile opportunities for gaining insights into the biomolecular processes occurring in donors, recipients, and grafts. To achieve this, adequate quality and numbers of biological samples are required. Whilst access to donor samples is facilitated by initiatives such as the QUOD biobank, an adequately powered biobank allowing exploration of recipient-related aspects in long-term transplant outcomes is missing. Rich, yet unverified resources of recipient material are the serum repositories present in the immunological laboratories of kidney transplant centers that prospectively collect recipient sera for immunological monitoring. However, it is yet unsure whether these samples are also suitable for -omics applications, since such clinical samples are collected and stored by individual centers using non-uniform protocols and undergo an undocumented number of freeze-thaw cycles. Whilst these handling and storage aspects may affect individual proteins and metabolites, it was reasoned that incidental handling/storage artifacts will have a limited effect on a theoretical network (pathway) analysis. To test the potential of such long-term stored clinical serum samples for pathway profiling, we submitted these samples to discovery proteomics and metabolomics. METHODS: A mass spectrometry-based shotgun discovery approach was used to obtain an overview of proteins and metabolites in clinical serum samples from the immunological laboratories of the Dutch PROCARE consortium. Parallel analyses were performed with material from the strictly protocolized QUOD biobank. RESULTS: Following metabolomics, more than 800 compounds could be identified in both sample groups, of which 163 endogenous metabolites were found in samples from both biorepositories. Proteomics yielded more than 600 proteins in both groups. Despite the higher prevalence of fragments in the clinical, non-uniformly collected samples compared to the biobanked ones (42.5% vs 26.5% of their proteomes, respectively), these fragments could still be connected to their parent proteins. Next, the proteomic and metabolomic profiles were successfully mapped onto theoretical pathways through integrated pathway analysis, which showed significant enrichment of 79 pathways. CONCLUSIONS: This feasibility study demonstrated that long-term stored serum samples from clinical biorepositories can be used for qualitative proteomic and metabolomic pathway analysis, a notion with far-reaching implications for all biomedical, long-term outcome-dependent research questions and studies focusing on rare events.
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BACKGROUND: Aspirin and other non-steroidal anti-inflammatory drugs (NSAIDs) usage has been associated with pancreatic ductal adenocarcinoma (PDAC) prevention, though epidemiological data have not reliably demonstrated this. The aim of this study is to identify if aspirin and other NSAIDs are effective in the primary prevention of PDAC in a large UK prospective cohort. METHODS: A nested case-control study was conducted using the UK Biobank cohort. Incident PDAC cases (n = 1129 of whom 239 (21.2 %) were using aspirin) were age and sex-matched with cancer-free controls (n = 8822 of whom 1752 (19.9 %) were using aspirin). Conditional logistic regression models were used to generate odds ratios (ORs) and 95 % confidence intervals (CI) for risk of PDAC with and without regular use of aspirin, non-aspirin NSAIDs and all NSAIDs respectively. Exploratory analyses were carried out assessing interactions with diabetes mellitus (DM) as a condition with increased pancreatic cancer risk. RESULTS: Regular aspirin use at initial recruitment was independently associated with a decreased risk of PDAC (OR [95 % CI] = 0.80 [0.68-0.95] P = 0.01). Regular non-aspirin NSAID use was not associated with a risk reduction of PDAC (OR [95 % CI] = 1.01 [0.84-1.23] P = 0.88). Exploratory analyses showed that in those with DM; regular aspirin use reduced risk of PDAC (OR [95 % CI] = 0.60 [0.42-0.85] P = 0.004) compared to non-use. DISCUSSION: Regular aspirin use is associated with a reduction in risk of PDAC. The reduced risk is more apparent in participants with DM.
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AIM: To evaluate the association of glycated haemoglobin (HbA1c) and serum glucose with intraocular pressure (IOP) in a large UK general population. MATERIALS AND METHODS: Participants were selected from the UK Biobank, excluding those with eye conditions that may affect IOP. IOP was measured using an ocular response analyser. Goldmann-correlated IOP (IOPg) and corneal-compensated IOP (IOPcc) were outcomes of interest, and ocular hypertension was defined as left-eye IOPg or IOPcc > 21 mmHg. HbA1c and random (non-fasting) serum glucose were the exposures of interest. Multivariate restricted cubic spline models, as well as linear regression, were applied to explore the associations of interest. RESULTS: Among 68 806 participants (46.5% male), the mean age was 56.7 years. The mean (standard deviation) for IOPg was 15.7 (3.6) mmHg and 15.9 (3.6) mmHg for IOPcc. Occular hypertension was prevalent in 8055 participants (11.7%) and 4178 participants (6.1%) had diabetes. Those with diabetes had higher IOP and a higher prevalence of ocular hypertension. After adjustment for demographic and clinical variables, HbA1c was positively associated with IOP in participants with diabetes, but not in those without diabetes. For every 10-mmol/mol increase in HbA1c, IOPg increased by 0.20 mmHg (95% confidence interval [CI] 0.12, 0.28) and IOPcc by 0.15 mmHg (95% CI 0.07, 0.23); the odds of ocular hypertension was increased by 6% (95% CI 1.00, 1.13) in participants with diabetes. A borderline positive association between serum glucose and IOP was found only in participants without diabetes. CONCLUSIONS: Impaired glycaemic control was associated with elevated IOP and a possible risk of ocular hypertension among participants with diabetes but of normal ocular health.
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Background: Although observational studies have reported several common biomarkers related to coronary artery disease (CAD) and cancer, there is a shortage of traditional epidemiological data to establish causative linkages. Thus, we conducted a comprehensive two-sample Mendelian randomization (MR) analysis to systematically investigate the causal associations of 109 traits with both CAD and cancer to identify their shared risk and protective factors. Methods: The genetic association datasets pertaining to exposure and outcomes were reviewed using the most recent and public genome-wide association studies (GWAS). Inverse variance weighting (IVW), weighted median (WM), and MR-Egger strategies were implemented for the MR analyses. The heterogeneity and pleiotropy were measured utilizing leave-one-out sensitivity testing, MR-PRESSO outlier detection, and Cochran's Q test. Results: The IVW analyses revealed that genetic-predicted mean sphered cell volume (MSCV) is a protective factor for CAD, and weight is a risk factor. MSCV and weight also show similar effects on cancer. Furthermore, our study also identified a set of risk and protective factors unique to CAD and cancer, such as telomere length. Conclusions: Our Mendelian randomization study sheds light on shared and unique risk and protective factors for CAD and cancer, offering valuable insights that could guide future research and the development of personalized strategies for preventing and treating these two significant health issues.
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BACKGROUND: Dietary flavonoids may have potential effects on hormone-related cancers (HRCs) due to their anti-cancer properties via regulating hormones and suppressing inflammation and oxidative stress. We aimed to examine the association of flavonoid intake with risks of HRCs and whether this association was mediated by blood biomarkers involved in biological mechanisms. METHODS: This prospective cohort study from UK Biobank included 187,350 participants free of cancer when the last dietary recall was completed. The dietary intakes of flavonoids and subclasses were assessed using 24-hour dietary recalls. Venous blood was collected at baseline and assayed for biomarkers of inflammation, hormones, and oxidative stress. Hazard ratios (HR) and 95 % confidential intervals (CI) for the associations between flavonoid intake and HRCs risk were estimated by the cause-specific Cox proportional hazards model. The role of blood biomarkers in the flavonoids-HRCs association was investigated through mediation analysis. RESULTS: Over a median follow-up of 9.5 years, 3,392 female breast cancer, 417 ovarian cancer, 516 endometrial cancer, 4,305 prostate cancer, 45 testicular cancer, and 146 thyroid cancer cases were documented. Compared to the lowest quintile, multivariable-adjusted HRs (95 % CIs) in the highest quintile of total flavonoid intake were 0.89 (0.80-0.99) for breast cancer, 0.68 (0.50-0.92) for ovarian cancer, and 0.88 (0.80-0.98) for female-specific cancers. For subclasses, intakes of flavonols and anthocyanidins were inversely associated with the risk of female-specific cancers (Ptrend <0.05). Anthocyanidin intake was positively related to prostate cancer risk, whereas isoflavone intake was inversely linked to thyroid cancer risk (Ptrend <0.05). Additionally, certain biomarkers of inflammation, hormones and oxidative stress jointly mediated the association of flavonoid intake with the risk of female-specific cancers and prostate cancer. CONCLUSIONS: Our findings highlighted the importance of dietary flavonoids for the prevention of HRCs in the general population, providing epidemiological evidence for dietary guidelines.
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BACKGROUND: The role of main work during the life course in predicting frailty, a typical geriatric syndrome, is still largely unknown. Therefore, with this research, we aimed to investigate the potential association between the main work done during the life with frailty and pre-frailty among participants 60 years and older of the UK Biobank study. METHODS: Frailty and pre-frailty presence were ascertained using a model including 5 indicators (weakness, slowness, weight loss, low physical activity, and exhaustion); the main employment status was ascertained using self-reported information. The association between frailty and main work was explored using an ordinal logistic regression model and reported as odds ratios (ORs) with their 95 % confidence intervals (CIs). RESULTS: The final sample comprised a total of 50,447 individuals (mean age: 64.2 years, females: 50.2 %). Individuals with higher qualifications had a reduced risk of frailty (OR = 0.881, 95%CI = 0.83-0.95, p-value<0.001 for pre-frail and OR = 0.681, 95%CI = 0.63-0.73, p-value<0.001 for frail) compared to those with lower qualifications. Moreover, active participation in the workforce, compared to being inactive, emerged as a protective factor from frailty (OR = 0.753, 95%CI = 0.70-0.81, p-value<0.001). The categories of Associate Professional and Technical Occupations exhibited protective effects against both pre-frailty and frailty. Similarly, occupations categorized as Professional and Management demonstrated protective effects against pre-frailty and frailty when compared to Elementary Occupations. Additionally, engagement in Trades and Services occupations, as opposed to Elementary Occupations, appeared to be protective against frailty. CONCLUSIONS: In this large cross-sectional investigation based on the data of the UK Biobank we found that work during lifetime could be an important factor in determining frailty later in life.
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BACKGROUND: Atrial fibrillation (AF) is the most common heart arrhythmia worldwide and is linked to a higher risk of mortality and morbidity. To predict AF and AF-related complications, clinical risk scores are commonly employed, but their predictive accuracy is generally limited, given the inherent complexity and heterogeneity of patients with AF. By classifying different presentations of AF into coherent and manageable clinical phenotypes, the development of tailored prevention and treatment strategies can be facilitated. In this study, we propose an artificial intelligence (AI)-based methodology to derive meaningful clinical phenotypes of AF in the general and critical care populations. METHODS: Our approach employs generative topographic mapping, a probabilistic machine learning method, to identify micro-clusters of patients with similar characteristics. It then identifies macro-cluster regions (clinical phenotypes) in the latent space using Ward's minimum variance method. We applied it to two large cohort databases (UK-Biobank and MIMIC-IV) representing general and critical care populations. FINDINGS: The proposed methodology showed its ability to derive meaningful clinical phenotypes of AF. Because of its probabilistic foundations, it can enhance the robustness of patient stratification. It also produced interpretable visualisation of complex high-dimensional data, enhancing understanding of the derived phenotypes and their key characteristics. Using our methodology, we identified and characterised clinical phenotypes of AF across diverse patient populations. INTERPRETATION: Our methodology is robust to noise, can uncover hidden patterns and subgroups, and can elucidate more specific patient profiles, contributing to more robust patient stratification, which could facilitate the tailoring of prevention and treatment programs specific to each phenotype. It can also be applied to other datasets to derive clinically meaningful phenotypes of other conditions. FUNDING: This study was funded by the DECIPHER project (LJMU QR-PSF) and the EU project TARGET (10113624).
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AIM: The purpose of this paper is to explore sex-based differences in cardiovascular health (CVH) and the incidence of type 2 diabetes mellitus (T2DM) among women at different menopausal stages and men. METHODS: A prospective cohort study was conducted, involving 126,818 participants without pre-existing T2DM from the UK Biobank. CVH was assessed using the Life's Essential 8. Absolute risks (ARs) and hazard ratios (HRs) were separately employed to assess the association between increased CVH and T2DM risk. The Accelerated Failure Time model assessed the impact of CVH on the time to T2DM onset. RESULTS: Over a mean follow-up of 168 months, 4,315 cases of T2DM were documented. In men, each one-point increase in CVH was associated with a 0.268% decrease in AR and a 6.4% decrease in HR for T2DM. In premenopausal, perimenopausal and postmenopausal women, each unit increase in CVH resulted in a 0.105%, 0.180% and 0.166% decrease in AR and a 7.7%, 5.2% and 6.4% decrease in HR of T2DM. The adjusted median time to T2DM onset was delayed by 12.46, 9.83, 11.5 and 21.43 months in the highest quintile of men, premenopausal, perimenopausal and postmenopausal women, respectively, compared with the lowest CVH quintile. CONCLUSIONS: As CVH improved, the reduction in AR for T2DM was more prominent in men than in women. HR trends for CVH and T2DM were similar in men and postmenopausal women. Increased CVH delayed the onset of T2MD in both men and women, with the most significant delay observed in postmenopausal women.
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BACKGROUND: Traditional cardiovascular risk factors, including hypertension, only explain part of major adverse cardiac events (MACE). Understanding what other risk factors contribute to MACE is essential for prevention. Constipation shares common risk factors with hypertension and is associated with an increased risk of several cardiovascular diseases. We hypothesised that constipation is an under-appreciated risk factor for MACE. METHODS: We used the population healthcare and genomic data in the UK Biobank (UKBB) (n=408,354) to study the contribution of constipation (ICD-10 K59.0) to the risk of MACE, defined by any episode of acute coronary syndrome (ACS), ischemic stroke and heart failure (HF). Analyses were controlled for traditional cardiovascular risk factors. We also assessed genetic correlations (rg) between constipation and MACE. RESULTS: Constipation cases (N=23,814) exhibited significantly higher risk of MACE compared to those with normal bowel habits (OR=2.15, P<1.00×10-300). Constipation was also significantly associated with individual MACE subgroups, in order: HF (OR=2.72, P<1.00×10-300), ischemic stroke (OR=2.36, P=2.02×10-230), and ACS (OR=1.62, P=5.82×10-113). In comparison with constipation-free hypertensive patients, hypertensives with constipation showed significantly higher odds of MACE (OR=1.68, P=1.05×10-136) and a 34% increased risk of MACE occurrence (P=2.3×10-50) after adjustment for medications that affect gut motility and other traditional cardiovascular risk factors. Finally, we detected positive genetic correlations between constipation and MACE subgroups ACS (rg=0.27, P=2.12×10-6), ischemic stroke (rg=0.23, P=0.011), and HF (rg=0.21, P=0.0062). CONCLUSION: We identified constipation as a potential risk factor independently associated with higher MACE prevalence. These findings warrant further studies on their causal relationship and identification of pathophysiological mechanisms.
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BACKGROUND: The relationship between serum uric acid (SUA) levels and brain-related health remains uncertain. OBJECTIVES: This study aimed to investigate the relationship between SUA levels and some neurodegenerative disorders and brain structure. DESIGN: A longitudinal study. SETTING AND PARTICIPANTS: 384,517 participants who did not have stroke, dementia, and Parkinsonism, with complete urate testes and covariates were included. MEASUREMENTS: Cox proportional hazards models, competing risk models, and restricted cubic spine models were applied. RESULTS: During the median follow-up time of 12.7 years (interquartile range [IQR]:12.0, 13.5), 7821 (2.0%) participants developed stroke, 5103 (1.3%) participants developed dementia, and 2341 (0.6%) participants developed Parkinsonism. Nonlinear relationships were identified between SUA levels and stroke (J-shaped), dementia, and Parkinsonism (U-shaped). SUA levels of 4.2 mg/dl, 6.4 mg/dl, and 6.6 mg/dl yielded the lowest risk of stroke, dementia, and Parkinsonism, respectively. Besides, we found high SUA levels reduced the volumes of total brain, grey matter, white matter, grey matter in the hippocampus, and hippocampus, but increased lateral-ventricle volume. Inflammation accounted for 9.1% and 10.0% in the association of SUA with stroke and lateral-ventricle volume. CONCLUSIONS: Lower SUA levels increased the risk of Parkinsonism, while both lower and higher SUA levels were positively associated with increased risk of stroke and dementia. Moreover, high SUA levels reduced brain structure volumes. Our findings suggest the association between SUA levels and brain-related disorders and highlight the importance of SUA management.
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BACKGROUND & AIMS: The role of circulating polyunsaturated fatty acids (PUFAs) in preventing liver cirrhosis complications remains unclear. METHODS: Between 2006 and 2010, 273,834 UK Biobank participants with plasma PUFA quantification data were enrolled and followed up until October 31, 2022. Plasma PUFAs were quantified using a high-throughput nuclear magnetic resonance-based metabolic profiling platform. Liver cirrhosis complications were defined as hospitalization for liver cirrhosis or presentation with hepatocellular carcinoma. RESULTS: During a median follow-up of 13.9 years, 2026 participants developed liver cirrhosis complications. Total plasma PUFAs, omega-3 PUFAs, docosahexaenoic acid (DHA), omega-6 PUFAs, and linoleic acid (LA) were inversely associated with the risk of liver cirrhosis complications, whereas the plasma omega-6/omega-3 ratio was positively associated. Nonparametrically restricted cubic spline regression showed nonlinear associations of plasma PUFAs with liver cirrhosis complications. The inflection points were 4.78 mmol/L for total PUFAs, 0.73 mmol/L for omega-3 PUFAs, 0.25 mmol/L for DHA, 4.07 mmol/L for omega-6 PUFAs, and 2.99 mmol/L for LA. Plasma omega-3 PUFAs were negatively associated with the risk of liver cirrhosis complications when omega-3 PUFAs were <0.73 mmol/L (adjusted hazard ratio [HR], 0.11 [0.08-0.16]), whereas the association was inverted when omega-3 PUFAs were ≥0.73 mmol/L (adjusted HR, 1.87 [1.20-2.92]). CONCLUSIONS: The protective effect of plasma omega-3 PUFAs on liver cirrhosis complications is reversed after passing the corresponding inflection point, suggesting an optimal dietary omega-3 PUFA supplementation dose.
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Biobanking provides benefit for future generations by facilitating medical research and subsequent translation and application of research findings. Long-term storage and research involving biological material and associated data necessitate the proper implementation of ethical and legal standards. A key principle includes recognizing informed consent as a crucial element for legitimizing the collection of biological material and data. Furthermore, any collected material and data must be employed exclusively for the research framework that aligns with the explicit consent provided by the participants. Last but not least, data privacy and security are essential in biobanking. This review elucidates chances and limitations of biobanking in the field of allogeneic hematopoietic cell transplantation. We discuss the practical implementation of the requirements, illustrated by the Collaborative Biobank, a collaborative research platform for research in blood cancer.
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Bancos de Espécimes Biológicos , Transplante de Células-Tronco Hematopoéticas , Humanos , Doadores de Tecidos , Consentimento Livre e Esclarecido , AloenxertosRESUMO
Genetic variants used as instruments for exposures in Mendelian randomisation (MR) analyses may have horizontal pleiotropic effects (i.e., influence outcomes via pathways other than through the exposure), which can undermine the validity of results. We examined the extent of this using smoking behaviours as an example. We first ran a phenome-wide association study in UK Biobank, using a smoking initiation genetic instrument. From the most strongly associated phenotypes, we selected those we considered could either plausibly or not plausibly be caused by smoking. We examined associations between genetic instruments for smoking initiation, smoking heaviness and lifetime smoking and these phenotypes in UK Biobank and the Avon Longitudinal Study of Parents and Children (ALSPAC). We conducted negative control analyses among never smokers, including children. We found evidence that smoking-related genetic instruments were associated with phenotypes not plausibly caused by smoking in UK Biobank and (to a lesser extent) ALSPAC. We observed associations with phenotypes among never smokers. Our results demonstrate that smoking-related genetic risk scores are associated with unexpected phenotypes that are less plausibly downstream of smoking. This may reflect horizontal pleiotropy in these genetic risk scores, and we would encourage researchers to exercise caution this when using these and genetic risk scores for other complex behavioural exposures. We outline approaches that could be taken to consider this and overcome issues caused by potential horizontal pleiotropy, for example, in genetically informed causal inference analyses (e.g., MR) it is important to consider negative control outcomes and triangulation approaches, to avoid arriving at incorrect conclusions.
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Background and aims: We aimed to study the association of very low serum Lipoprotein(a) [Lp(a)] concentrations with new-onset type 2 diabetes (T2D) and non-alcoholic liver disease (NAFLD) in the context of statin usage in the UK Biobank, a large prospective population cohort. Methods: Using an extended biomarker dataset, we identified 47,362 participants with very low Lp(a) concentrations (<3.8 nmol/L) from a total of 451,479 participants. With a median follow-up of 12.3 years, we assessed the risk of new-onset cardiometabolic diseases in participants stratified by statin usage with Cox proportional hazards models. We performed two-sample Mendelian randomization MR analyses to test causal relationship between genetically predicted Lp(a) and T2D and NAFLD. Results: Taking the participants with Lp(a) within reportable range as the reference group, the hazard ratios (HR) for T2D were 1.07 (95 % confidence interval, CI 1.01-1.13) and for NAFLD 1.30 (95 % CI 1.20-1.41) respectively for participants with very low Lp(a) (<3.8 nmol/L). The risk for new-onset T2D was higher in participants using statins (adjusted HR 1.15; 95 % CI 1.05-1.27). The risk estimates for new-onset NAFLD were comparable in the analysis stratified by statin use. There was no evidence for causal links between genetically predicted Lp(a) and T2D nor NAFLD in two-sample MR analyses. Conclusions: Very low Lp(a) was associated with higher risks of T2D and NAFLD in a prospective analysis of the UK Biobank. The association with T2D was influenced by lipid lowering medication usage. MR analyses did not support causality for these inverse associations.
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BACKGROUND: Although previous studies have identified specific circulating inflammatory markers associated with the risk of mortality, they have often overlooked the broader impact of a comprehensive inflammatory response on health outcomes. This study aims to assess the association between circulating systemic inflammation and age-related hospitalization and premature death, as well as explore the potential mediating effects of various dietary patterns on these associations. METHODS: A total of 448,574 participants enrolled in the UK Biobank study were included. Circulating C-reactive protein(CRP), white blood cell count(WBC), platelet count(Plt), and neutrophil/lymphocyte ratio(NLR) were measured, which were used to establish a weighted systemic inflammatory index of inflammation index(INFLA-Score). Dietary intake information was documented through 24-hour dietary recalls, and dietary pattern scores including Dietary Approaches to Stop Hypertension(DASH), Mediterranean(MED), and Healthy Eating Index-2020(HEI-2020) were calculated. Cox proportional hazards regression models were performed to assess the associations between INFLA-Score and age-related disease hospitalization, cause-specific and all-cause premature death. RESULTS: During a median follow-up of 12.65 years, 23,784 premature deaths were documented. After adjusting for multiple covariates, higher levels of CRP, WBC, NLR, and INFLA-Score were significantly associated with increased risks of age-related disease hospitalization(HRCRP=1.19; 95%:1.17-1.21; HRWBC=1.17; 95%:1.15-1.19; HRNLR=1.18; 95%:1.16-1.20; HRINFLA-Score=1.19; 95%:1.17-1.21) and premature death(HRCRP=1.68; 95%:1.61-1.75; HRWBC=1.23; 95%:1.18-1.27; HRNLR=1.45; 95%:1.40-1.50; HRINFLA-Score=1.58; 95%:1.52-1.64). Compared to the lowest INFLA-Score group, the highest INFLA-Score group was associated with increased values of whole-body and organ-specific biological age, and had a shortened life expectancy of 2.96 (95% CI 2.53-3.41) and 4.14 (95% CI 3.75-4.56) years at the age of 60 years in women and men, respectively. Additionally, we observed no significant association of the INFLA-Score with aging-related hospitalization and premature death among participants who were more adhering to the Mediterranean (MED) dietary pattern(HRAging-related hospitalization=1.07; 95%:0.99-1.16;HRPremature death=1.19; 95%:0.96-1.47). CONCLUSION: A higher INFLA-Score was correlated with an increased risk of age-related hospitalization and premature death. Nevertheless, adherence to a Mediterranean (MED) diet may mitigate these associations.
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Bancos de Espécimes Biológicos , Dieta Mediterrânea , Inflamação , Mortalidade Prematura , Humanos , Reino Unido/epidemiologia , Feminino , Masculino , Dieta Mediterrânea/estatística & dados numéricos , Pessoa de Meia-Idade , Inflamação/sangue , Estudos Prospectivos , Idoso , Adulto , Hospitalização/estatística & dados numéricos , Proteína C-Reativa/análise , Biomarcadores/sangue , Biobanco do Reino UnidoRESUMO
BACKGROUND: Accumulating evidence suggests that cardiovascular diseases and breast cancer share a number of common risk factors, however, evidence on the association between cardiovascular health (CVH) and breast cancer is limited. The present study aimed to assess the association of CVH, defined by Life's Essential 8 (LE8) and genetic risk with breast cancer incidence and mortality among premenopausal and postmenopausal women. METHODS: We used data from the UK Biobank and conducted the multivariate Cox proportional-hazards models to examine associations of LE8 score and genetic risk with breast cancer incidence and mortality. Date on LE8 score was collected between 2006 and 2010 and composed of eight components, including behavioral metrics (diet, tobacco or nicotine exposure, physical activity, and sleep health), and biological metrics (body mass index, blood lipids, blood glucose, and blood pressure). The polygenic risk score (PRS) was calculated as the sum of effect sizes of individual genetic variants multiplied by the allele dosage. RESULTS: A total of 150,566 premenopausal and postmenopausal women were included. Compared to postmenopausal women with low LE8 score, those with high LE8 score were associated with 22% lower risk of breast cancer incidence (HR: 0.78, 95% CI: 0.70-0.87) and 43% lower risk of breast cancer mortality (HR: 0.57, 95% CI: 0.36-0.90). By contrast, we did not observe the significant association among premenopausal women. Further analyses stratified by PRS categories showed that high LE8 score was associated with 28% and 71% decreased risk of breast cancer incidence (HR: 0.72, 95% CI: 0.60-0.87) and mortality (HR: 0.29, 95% CI: 0.10-0.83) compared to low LE8 score among high genetic risk groups, but no significant associations were found among low genetic risk groups. Furthermore, compared with postmenopausal women with high LE8 score and low genetic risk, those with low LE8 score and high genetic risk were associated with increased risk of breast cancer incidence (HR: 6.26, 95% CI: 4.43-8.84). CONCLUSIONS: The present study suggests that better CVH is a protective factor for both breast cancer incidence and mortality among postmenopausal women. Moreover, the risk of developing breast cancer caused by high genetic susceptibility could be largely offset by better CVH.
Assuntos
Neoplasias da Mama , Doenças Cardiovasculares , Predisposição Genética para Doença , Humanos , Feminino , Neoplasias da Mama/genética , Neoplasias da Mama/mortalidade , Neoplasias da Mama/epidemiologia , Pessoa de Meia-Idade , Incidência , Estudos Prospectivos , Doenças Cardiovasculares/epidemiologia , Doenças Cardiovasculares/mortalidade , Doenças Cardiovasculares/genética , Fatores de Risco , Adulto , Pós-Menopausa , Idoso , Reino Unido/epidemiologia , Pré-Menopausa , Modelos de Riscos ProporcionaisRESUMO
BACKGROUND: The temporal relationships across cardiometabolic diseases (CMDs) were recently conceptualized as the cardiometabolic continuum (CMC), sequence of cardiovascular events that stem from gene-environmental interactions, unhealthy lifestyle influences, and metabolic diseases such as diabetes, and hypertension. While the physiological pathways linking metabolic and cardiovascular diseases have been investigated, the study of the sex and population differences in the CMC have still not been described. METHODS: We present a machine learning approach to model the CMC and investigate sex and population differences in two distinct cohorts: the UK Biobank (17,700 participants) and the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) (7162 participants). We consider the following CMDs: hypertension (Hyp), diabetes (DM), heart diseases (HD: angina, myocardial infarction, or heart failure), and stroke (STK). For the identification of the CMC patterns, individual trajectories with the time of disease occurrence were clustered using k-means. Based on clinical, sociodemographic, and lifestyle characteristics, we built multiclass random forest classifiers and used the SHAP methodology to evaluate feature importance. RESULTS: Five CMC patterns were identified across both sexes and cohorts: EarlyHyp, FirstDM, FirstHD, Healthy, and LateHyp, named according to prevalence and disease occurrence time that depicted around 95%, 78%, 75%, 88% and 99% of individuals, respectively. Within the UK Biobank, more women were classified in the Healthy cluster and more men in all others. In the EarlyHyp and LateHyp clusters, isolated hypertension occurred earlier among women. Smoking habits and education had high importance and clear directionality for both sexes. For ELSA-Brasil, more men were classified in the Healthy cluster and more women in the FirstDM. The diabetes occurrence time when followed by hypertension was lower among women. Education and ethnicity had high importance and clear directionality for women, while for men these features were smoking, alcohol, and coffee consumption. CONCLUSIONS: There are clear sex differences in the CMC that varied across the UK and Brazilian cohorts. In particular, disadvantages regarding incidence and the time to onset of diseases were more pronounced in Brazil, against woman. The results show the need to strengthen public health policies to prevent and control the time course of CMD, with an emphasis on women.