Higher habitual intakes of flavonoids and flavonoid-rich foods are associated with a lower incidence of type 2 diabetes in the UK Biobank cohort.

AIM: To examine the associations of a diet high in flavonoid-rich foods, as reflected by a "Flavodiet Score" (FDS), the major individual food contributors to flavonoid intake, and flavonoid subclasses with type 2 diabetes (T2D) risk in the UK Biobank cohort. MATERIALS AND METHODS: Flavonoid intakes were estimated from ≥2 dietary assessments among 113,097 study participants [age at enrolment: 56 ± 8 years; 57% female] using the U.S Department of Agriculture (USDA) databases. Multivariable Cox proportional hazards models were used to investigate associations between dietary exposures and T2D. RESULTS: During 12 years of follow-up, 2628 incident cases of T2D were identified. A higher FDS (compared to lower [Q4 vs. Q1]), characterised by an average of 6 servings of flavonoid-rich foods per day, was associated with a 26% lower T2D risk [HR: 0.74 (95% CI: 0.66-0.84), ptrend = <0.001]. Mediation analyses showed that lower body fatness and basal inflammation, as well as better kidney and liver function partially explain this association. In food-based analyses, higher intakes of black or green tea, berries, and apples were significantly associated with 21%, 15%, and 12% lower T2D risk. Among individual flavonoid subclasses, 19-28% lower risks of T2D were observed among those with the highest, compared to lowest intakes. CONCLUSIONS: A higher consumption of flavonoid-rich foods was associated with lower T2D risk, potentially mediated by benefits to obesity/sugar metabolism, inflammation, kidney and liver function. Achievable increases in intakes of specific flavonoid-rich foods have the potential to reduce T2D risk.

Exploring biorepository donation patterns, experiences, and recommendations: a mixed-methods study among Appalachian adults enrolled in a sugary drink reduction program.

Background: Under-represented subgroups in biomarker research linked to behavioral health trials may impact the promise of precision health. This mixed methods study examines biorepository donations across an Appalachian sample enrolled in a sugary drink reduction intervention trial. Methods: Participants enrolled in the behavioral trial were asked to join an optional biomarker study and were tracked for enrollment and biospecimen returns (stool and/or buccal sample). At 6 months, participants completed a summative interview on decision-making process, experiences collecting samples, and recommendations to encourage biospecimen donation. Return rates were analyzed across demographics (i.e., age, gender, race, education, income, health literacy status, and rurality status) using chi-squares. Qualitative data were content coded with differences compared by biomarker study enrollment and donation choices. Results: Of the 249 invited participants, 171 (61%) enrolled, and 63% (n = 157) returned buccal samples and 49% (n = 122) returned stool samples. Metro residing participants were significantly more likely (56%) to return stool samples compared to non-metro (39%) counterparts [x2(1) = 6.61; p = 0.01]. Buccal sample return had a similar trend, 67 and 57%, respectively for metro vs. non-metro [x2(1) = 2.84; p = 0.09]. An additional trend indicated that older (≥40 years) participants were more likely (55%) to donate stool samples than younger (43%) participants [x2(1) = 3.39; p = 0.07]. No other demographics were significantly associated with biospecimen return. Qualitative data indicated that societal (66-81%) and personal (41-51%) benefits were the most reported reasons for deciding to donate one or both samples, whereas mistrust (3-11%) and negative perceptions of the collection process (44-71%) were cited the most by those who declined one or both samples. Clear instructions (60%) and simple collection kits (73%) were donation facilitators while challenges included difficult stool collection kits (16%) and inconveniently located FedEx centers (16%). Recommendations to encourage future biorepository donation were to clarify benefits to science and others (58%), provide commensurate incentives (25%), explain purpose (19%) and privacy protections (20%), and assure ease in sample collection (19%). Conclusion: Study findings suggest the need for biomarker research awareness campaigns. Researchers planning for future biomarker studies in medically underserved regions, like Appalachia, may be able to apply findings to optimize enrollment.

Establishment of a Biorepository for Down Syndrome: Experience of the Inter-Institutional Multidisciplinary BioBank - BioBIM.

BACKGROUND: Down syndrome, or Trisomy 21, is the leading genetic cause of cognitive disability in children and is associated with a high risk of several comorbidities, particularly congenital heart defects, early onset Alzheimer's disease, leukaemia, and autoimmune disorders. OBJECTIVE: This study describes the design, methods, and operational procedures employed to establish a biobank dedicated to Down syndrome that can support research projects investigating the effects of various genetic and environmental factors on this complex disease. METHODS: Blood was collected from all recruited subjects, processed, aliquoted and immediately frozen at -80 °C in the Interinstitutional Multidisciplinary BioBank (BioBIM) facilities. A small aliquot of the sample was used to perform blood tests for which analysis would not be feasible at a later date, such as blood cell counts. Each biological sample was coded, assigned a Standard PREanalytical Code, and registered in the oloBIOBANK software connected to a medical card containing all the donor's anamnestic data. All samples were stored under continuous real-time temperature recording using a freezer connected to a T-GUARD alarm system. In addition, a radiofrequency identification tracking system strictly monitored each cryopreservation operation performed throughout the sample lifecycle. RESULTS: Biological samples were collected from 454 individuals with Down syndrome from 2007 to 2023. A total of 2233 biological samples were available for research purposes, including whole blood in different anticoagulants, serum, plasma, and frozen peripheral blood mononuclear cells. The quality of the nucleic acids obtained through specific standard operating procedures demonstrated that these samples were appropriate for clinical and basic research. CONCLUSION: By establishing this biobank, we have gathered a significant number of biological samples and clinical data from individuals with Down syndrome, thereby fostering collaboration between different research groups in an open and transparent manner. Sharing expertise and resources among scientists will ultimately facilitate the transfer of knowledge to clinical practice, leading to the development of more effective therapeutic treatments to improve the outcomes and quality of life of patients with Down syndrome.

Prospective associations of leucocyte subtypes and obesity with the risk of developing cutaneous malignant melanoma in the UK Biobank cohort.

BACKGROUND: Obesity is associated with chronic low-grade inflammation, which is linked to cancer development. Abdominal obesity (a body mass index, ABSI), however, has unusually been associated inversely with cutaneous malignant melanoma (CMM), while general obesity (body mass index, BMI) is associated positively. Leucocytes participate in inflammation and are higher in obesity, but prospective associations of leucocytes with cutaneous malignant melanoma are unclear. METHODS: We examined the prospective associations of neutrophil, lymphocyte, and monocyte counts (each individually), as well as the prospective associations of ABSI and BMI, with cutaneous malignant melanoma in UK Biobank. We used multivariable Cox proportional hazards models and explored heterogeneity according to sex, menopausal status, age (≥ 50 years at recruitment), smoking status, ABSI (dichotomised at the median: ≥73.5 women; ≥79.8 men), BMI (normal weight, overweight, obese), and time to diagnosis. RESULTS: During a mean follow-up of 10.2 years, 2174 CMM cases were ascertained in 398,450 participants. There was little evidence for associations with neutrophil or lymphocyte counts. Monocyte count, however, was associated inversely in participants overall (HR = 0.928; 95%CI: 0.888-0.971; per one standard deviation increase; SD = 0.144*109/L women; SD = 0.169*109/L men), specifically in older participants (HR = 0.906; 95%CI: 0.862-0.951), and more clearly in participants with low ABSI (HR = 0.880; 95%CI: 0.824-0.939), or with BMI ≥ 25 kg/m2 (HR = 0.895; 95%CI: 0.837-0.958 for overweight; HR = 0.923; 95%CI: 0.848-1.005 for obese). ABSI was associated inversely in pre-menopausal women (HR = 0.810; 95%CI: 0.702-0.935; SD = 4.95) and men (HR = 0.925; 95%CI: 0.867-0.986; SD = 4.11). BMI was associated positively in men (HR = 1.148; 95%CI: 1.078-1.222; SD = 4.04 kg/m2). There was little evidence for heterogeneity according to smoking status. The associations with monocyte count and BMI were retained to at least 8 years prior to diagnosis, but the association with ABSI was observed up to 4 years prior to diagnosis and not for longer follow-up time. CONCLUSIONS: Monocyte count is associated prospectively inversely with the risk of developing CMM in older individuals, while BMI is associated positively in men, suggesting a mechanistic involvement of factors related to monocytes and subcutaneous adipose tissue in melanoma development. An inverse association with ABSI closer to diagnosis may reflect reverse causality or glucocorticoid resistance.

Biobank-wide association scan identifies risk factors for late-onset Alzheimer's disease and endophenotypes.

Rich data from large biobanks, coupled with increasingly accessible association statistics from genome-wide association studies (GWAS), provide great opportunities to dissect the complex relationships among human traits and diseases. We introduce BADGERS, a powerful method to perform polygenic score-based biobank-wide association scans. Compared to traditional approaches, BADGERS uses GWAS summary statistics as input and does not require multiple traits to be measured in the same cohort. We applied BADGERS to two independent datasets for late-onset Alzheimer's disease (AD; n=61,212). Among 1738 traits in the UK biobank, we identified 48 significant associations for AD. Family history, high cholesterol, and numerous traits related to intelligence and education showed strong and independent associations with AD. Furthermore, we identified 41 significant associations for a variety of AD endophenotypes. While family history and high cholesterol were strongly associated with AD subgroups and pathologies, only intelligence and education-related traits predicted pre-clinical cognitive phenotypes. These results provide novel insights into the distinct biological processes underlying various risk factors for AD.

Circulating metabolic biomarkers and risk of new-onset hypertension: findings from the UK Biobank.

OBJECTIVE: The evidence regarding the associations of circulating metabolic biomarkers with hypertension risk is scarce. We aimed to examine the associations between circulating metabolites and risk of hypertension. METHODS: We included 49 422 individuals free of hypertension at baseline with a mean (SD) age of 53.5 (8.0) years from the UK Biobank. Nuclear magnetic resonance spectroscopy was used to quantify 143 individual metabolites. Multivariable-adjusted Cox regression models were used to estimate hazard ratios and 95% confidence intervals (CIs). RESULTS: During a mean (SD) follow-up of 11.2 (1.8) years, 2686 incident hypertension cases occurred. Out of 143 metabolites, 76 were associated with incident hypertension, among which phenylalanine (hazard ratio: 1.40; 95% CI: 1.24-1.58) and apolipoprotein A1 (hazard ratio: 0.76; 95% CI: 0.66-0.87) had the strongest association when comparing the highest to the lowest quintile. In general, very-low-density lipoprotein (VLDL) particles were positively, whereas high-density lipoprotein (HDL) particles were inversely associated with risk of hypertension. Similar patterns of cholesterol, phospholipids, and total lipids within VLDL and HDL particles were observed. Triglycerides within all lipoproteins were positively associated with hypertension risk. Other metabolites showed significant associations with risk of hypertension included amino acids, fatty acids, ketone bodies, fluid balance and inflammation markers. Adding 10 selected metabolic biomarkers to the traditional hypertension risk model modestly improved discrimination (C-statistic from 0.745 to 0.752, P < 0.001) for prediction of 10-year hypertension incidence. CONCLUSION: Among UK adults, disturbances in metabolic biomarkers are associated with incident hypertension. Comprehensive metabolomic profiling may provide potential novel biomarkers to identify high-risk individuals.

Interaction of physical activity and low-level air pollution on cardiovascular disease: a prospective cohort study in UK Biobank.

To investigate the associations of physical activity (PA), low-level air pollution, and interaction on cardiovascular diseases (CVD) incidence based on the UK Biobank. PA was measured by the International Physical Activity Questionnaire and five air pollutants were estimated using Land Use Regression. All association estimates were based on Cox regression. Dose-response relationship was explored by restricted cubic spline, while multiplicative and additive interaction were examined by Pinteraction and relative excess risk due to interaction (RERI). As deviating proportional hazards assumption, we analyzed data as follow-up < 4 years and ≥ 4 years, separately. PA with 1000-4000 Metabolic Equivalent Task (MET) min/week showed the strongest protective impact on CVD incidence, while only low-level nitrogen dioxides (NO2) showed negative impact among five air pollutants and was considered for further analysis. Multiplicative interaction between PA and NO2 was observed during ≥ 4 years follow-up (Pinteraction = 0.049) while not during < 4 years (Pinteraction = 0.290). Positive additive interactions were found for high PA and low NO2 (< 20 µg/m3) group (RERI: 0.07, 95% confidence intervals: 0.02-0.11) during < 4 years, and for moderate PA with NO2 at 40- µg/m3 (0.07, 0.02-0.13) and < 20 µg/m3 (0.07, 0.02-0.12), while high PA showed similar results with NO2 at 40-, 20- and < 20 µg/m3 during ≥ 4 years. PA about 1000-4000 METs min/week showed the lowest CVD risk. Possibility of interaction with PA and NO2 is more likely to present with the increase in follow-up duration. We call for the optimal thresholds of PA, and exploring interaction thoroughly by considering types of PA.

Quality of plant-based diets and frailty incidence: a prospective analysis of UK biobank participants.

BACKGROUND: Substantial evidence supports the inverse association between adherence to healthy dietary patterns and frailty risk. However, the role of plant-based diets, particularly their quality, is poorly known. OBJECTIVE: To examine the association of two plant-based diets with incidence of physical frailty in middle-aged and older adults. DESIGN: Prospective cohort. SETTING: United Kingdom. SUBJECTS: 24,996 individuals aged 40-70 years, followed from 2009-12 to 2019-22. METHODS: Based on at least two 24-h diet assessments, we built two diet indices: (i) the healthful Plant-based Diet Index (hPDI) and (ii) the unhealthful Plant-based Diet Index (uPDI). Incident frailty was defined as developing ≥3 out of 5 of the Fried criteria. We used Cox models to estimate relative risks (RR), and their 95% confidence interval (CI), of incident frailty adjusted for the main potential confounders. RESULTS: After a median follow-up of 6.72 years, 428 cases of frailty were ascertained. The RR (95% CI) of frailty was 0.62 (0.48-0.80) for the highest versus lowest tertile of the hPDI and 1.61 (1.26-2.05) for the uPDI. The consumption of healthy plant foods was associated with lower frailty risk (RR per serving 0.93 (0.90-0.96)). The hPDI was directly, and the uPDI inversely, associated with higher risk of low physical activity, slow walking speed and weak hand grip, and the uPDI with higher risk of exhaustion. CONCLUSIONS: In British middle-age and older adults, greater adherence to the hPDI was associated with lower risk of frailty, whereas greater adherence to the uPDI was associated with higher risk.

Reweighting UK Biobank corrects for pervasive selection bias due to volunteering.

BACKGROUND: Biobanks typically rely on volunteer-based sampling. This results in large samples (power) at the cost of representativeness (bias). The problem of volunteer bias is debated. Here, we (i) show that volunteering biases associations in UK Biobank (UKB) and (ii) estimate inverse probability (IP) weights that correct for volunteer bias in UKB. METHODS: Drawing on UK Census data, we constructed a subsample representative of UKB's target population, which consists of all individuals invited to participate. Based on demographic variables shared between the UK Census and UKB, we estimated IP weights (IPWs) for each UKB participant. We compared 21 weighted and unweighted bivariate associations between these demographic variables to assess volunteer bias. RESULTS: Volunteer bias in all associations, as naively estimated in UKB, was substantial-in some cases so severe that unweighted estimates had the opposite sign of the association in the target population. For example, older individuals in UKB reported being in better health, in contrast to evidence from the UK Census. Using IPWs in weighted regressions reduced 87% of volunteer bias on average. Volunteer-based sampling reduced the effective sample size of UKB substantially, to 32% of its original size. CONCLUSIONS: Estimates from large-scale biobanks may be misleading due to volunteer bias. We recommend IP weighting to correct for such bias. To aid in the construction of the next generation of biobanks, we provide suggestions on how to best ensure representativeness in a volunteer-based design. For UKB, IPWs have been made available.

Phenome-wide identification of therapeutic genetic targets, leveraging knowledge graphs, graph neural networks, and UK Biobank data.

The ongoing expansion of human genomic datasets propels therapeutic target identification; however, extracting gene-disease associations from gene annotations remains challenging. Here, we introduce Mantis-ML 2.0, a framework integrating AstraZeneca's Biological Insights Knowledge Graph and numerous tabular datasets, to assess gene-disease probabilities throughout the phenome. We use graph neural networks, capturing the graph's holistic structure, and train them on hundreds of balanced datasets via a robust semi-supervised learning framework to provide gene-disease probabilities across the human exome. Mantis-ML 2.0 incorporates natural language processing to automate disease-relevant feature selection for thousands of diseases. The enhanced models demonstrate a 6.9% average classification power boost, achieving a median receiver operating characteristic (ROC) area under curve (AUC) score of 0.90 across 5220 diseases from Human Phenotype Ontology, OpenTargets, and Genomics England. Notably, Mantis-ML 2.0 prioritizes associations from an independent UK Biobank phenome-wide association study (PheWAS), providing a stronger form of triaging and mitigating against underpowered PheWAS associations. Results are exposed through an interactive web resource.

Omeprazole and risk of osteoarthritis: insights from a mendelian randomization study in the UK Biobank.

BACKGROUND: A former cohort study has raised concern regarding the unanticipated hazard of omeprazole in expediting osteoarthritis (OA) advancement. The precise nature of their causal evidence, however, remains undetermined. The present research endeavors to investigate the underlying causal link between omeprazole and OA through the application of mendelian randomization (MR) analysis. METHODS: The study incorporated the ukb-a-106 and ukb-b-14,486 datasets. The investigation of causal effects employed methodologies such as MR-Egger, Weighted median, Inverse variance weighted (IVW) with multiplicative random effects, and IVW (fixed effects). The IVW approach was predominantly considered for result interpretation. Sensitivity analysis was conducted, encompassing assessments for heterogeneity, horizontal pleiotropy, and the Leave-one-out techniques. RESULTS: The outcomes of the MR analysis indicated a causal relationship between omeprazole and OA, with omeprazole identified as a contributing risk factor for OA development (IVW model: OR = 1.2473, P < 0.01 in ukb-a-106; OR = 1.1288, P < 0.05 in ukb-b-14,486). The sensitivity analysis underscored the robustness and dependability of the above-mentioned analytical findings. CONCLUSION: This study, employing MR, reveals that omeprazole, as an exposure factor, elevates the risk of OA. Considering the drug's efficacy and associated adverse events, clinical practitioners should exercise caution regarding prolonged omeprazole use, particularly in populations with heightened OA risks. Further robust and high-quality research is warranted to validate our findings and guide clinical practice.

An epidemiological study of season of birth, mental health, and neuroimaging in the UK Biobank.

Environmental exposures during the perinatal period are known to have a long-term effect on adult physical and mental health. One such influential environmental exposure is the time of year of birth which affects the amount of daylight, nutrients, and viral load that an individual is exposed to within this key developmental period. Here, we investigate associations between season of birth (seasonality), four mental health traits (n = 137,588) and multi-modal neuroimaging measures (n = 33,212) within the UK Biobank. Summer births were associated with probable recurrent Major Depressive Disorder (ß = 0.026, pcorr = 0.028) and greater mean cortical thickness in temporal and occipital lobes (ß = 0.013 to 0.014, pcorr<0.05). Winter births were associated with greater white matter integrity globally, in the association fibers, thalamic radiations, and six individual tracts (ß = -0.013 to -0.022, pcorr<0.05). Results of sensitivity analyses adjusting for birth weight were similar, with an additional association between winter birth and white matter microstructure in the forceps minor and between summer births, greater cingulate thickness and amygdala volume. Further analyses revealed associations between probable depressive phenotypes and a range of neuroimaging measures but a paucity of interactions with seasonality. Our results suggest that seasonality of birth may affect later-life brain structure and play a role in lifetime recurrent Major Depressive Disorder. Due to the small effect sizes observed, and the lack of associations with other mental health traits, further research is required to validate birth season effects in the context of different latitudes, and by co-examining genetic and epigenetic measures to reveal informative biological pathways.

Body mass index and all-cause mortality in HUNT and UK biobank studies: revised non-linear Mendelian randomisation analyses.

OBJECTIVES: To estimate the shape of the causal relationship between body mass index (BMI) and mortality risk in a Mendelian randomisation framework. DESIGN: Mendelian randomisation analyses of two prospective population-based cohorts. SETTING: Individuals of European ancestries living in Norway or the UK. PARTICIPANTS: 56 150 participants from the Trøndelag Health Study (HUNT) in Norway and 366 385 participants from UK Biobank recruited by postal invitation. OUTCOMES: All-cause mortality and cause-specific mortality (cardiovascular, cancer, non-cardiovascular non-cancer). RESULTS: A previously published non-linear Mendelian randomisation analysis of these data using the residual stratification method suggested a J-shaped association between genetically predicted BMI and mortality outcomes with the lowest mortality risk at a BMI of around 25 kg/m2. However, the 'constant genetic effect' assumption required by this method is violated. The reanalysis of these data using the more reliable doubly-ranked stratification method provided some indication of a J-shaped relationship, but with much less certainty as there was less precision in estimates at the lower end of the BMI distribution. Evidence for a harmful effect of reducing BMI at low BMI levels was only present in some analyses, and where present, only below 20 kg/m2. A harmful effect of increasing BMI for all-cause mortality was evident above 25 kg/m2, for cardiovascular mortality above 24 kg/m2, for cancer mortality above 30 kg/m2 and for non-cardiovascular non-cancer mortality above 26 kg/m2. In UK Biobank, the association between genetically predicted BMI and mortality at high BMI levels was stronger in women than in men. CONCLUSION: This research challenges findings from previous conventional observational epidemiology and Mendelian randomisation investigations that the lowest level of mortality risk is at a BMI level of around 25 kg/m2. Our results provide some evidence that reductions in BMI will increase mortality risk for a small proportion of the population, and clear evidence that increases in BMI will increase mortality risk for those with BMI above 25 kg/m2.

Modifiable lifestyle factors and lifetime risk of atrial fibrillation: longitudinal data from the Korea NHIS-HealS and UK Biobank cohorts.

BACKGROUND: The reason for higher incidence of atrial fibrillation (AF) in Europe compared with East Asia is unclear. We aimed to investigate the association between modifiable lifestyle factors and lifetime risk of AF in Europe and East Asia, along with race/ethnic similarities and disparities. METHODS: 1:1 propensity score matched pairs of 242,763 East Asians and 242,763 White Europeans without AF were analyzed. Modifiable lifestyle factors considered were blood pressure, body mass index, cigarette smoking, diabetes, alcohol consumption, and physical activity, categorized as non-adverse or adverse levels. Lifetime risk of AF was estimated from the index age of 45 years to the attained age of 85 years, accounting for the competing risk of death. RESULTS: The overall lifetime risk of AF was higher in White Europeans than East Asians (20.9% vs 15.4%, p < 0.001). The lifetime risk of AF was similar between the two races in individuals with non-adverse lifestyle factor profiles (13.4% vs 12.9%, p = 0.575), whereas it was higher in White Europeans with adverse lifestyle factor profiles (22.1% vs 15.8%, p < 0.001). The difference in the lifetime risk of AF between the two races increased as the burden of adverse lifestyle factors worsened (1 adverse lifestyle factor; 4.3% to ≥ 3 adverse lifestyle factors; 11.2%). Compared with East Asians, the relative risk of AF in White Europeans was 23% and 62% higher for one (hazard ratio [HR] 1.23, 95% confidence interval [CI] 1.16-1.29) and ≥ 3 adverse lifestyle factors (HR 1.62, 95% CI 1.51-1.75), respectively. CONCLUSIONS: The overall higher lifetime risk of AF in White Europeans compared with East Asians might be attributable to adverse lifestyle factors. Adherence to healthy lifestyle factors was associated with the lifetime risk of AF of about 1 in 8 regardless of race/ethnicity.

Peripheral GFAP and NfL as early biomarkers for dementia: longitudinal insights from the UK Biobank.

BACKGROUND: Peripheral glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) are sensitive markers of neuroinflammation and neuronal damage. Previous studies with highly selected participants have shown that peripheral GFAP and NfL levels are elevated in the pre-clinical phase of Alzheimer's disease (AD) and dementia. However, the predictive value of GFAP and NfL for dementia requires more evidence from population-based cohorts. METHODS: This was a prospective cohort study to evaluate UK Biobank participants enrolled from 2006 to 2010 using plasma GFAP and NfL measurements measured by Olink Target Platform and prospectively followed up for dementia diagnosis. Primary outcome was the risk of clinical diagnosed dementia. Secondary outcomes were cognition. Linear regression was used to assess the associations between peripheral GFAP and NfL with cognition. Cox proportional hazard models with cross-validations were used to estimate associations between elevated GFAP and NfL with risk of dementia. All models were adjusted for covariates. RESULTS: A subsample of 48,542 participants in the UK Biobank with peripheral GFAP and NfL measurements were evaluated. With an average follow-up of 13.18 ± 2.42 years, 1312 new all-cause dementia cases were identified. Peripheral GFAP and NfL increased up to 15 years before dementia diagnosis was made. After strictly adjusting for confounders, increment in NfL was found to be associated with decreased numeric memory and prolonged reaction time. A greater annualized rate of change in GFAP was significantly associated with faster global cognitive decline. Elevation of GFAP (hazard ratio (HR) ranges from 2.25 to 3.15) and NfL (HR ranges from 1.98 to 4.23) increased the risk for several types of dementia. GFAP and NfL significantly improved the predictive values for dementia using previous models (area under the curve (AUC) ranges from 0.80 to 0.89, C-index ranges from 0.86 to 0.91). The AD genetic risk score and number of APOE*E4 alleles strongly correlated with GFAP and NfL levels. CONCLUSIONS: These results suggest that peripheral GFAP and NfL are potential biomarkers for the early diagnosis of dementia. In addition, anti-inflammatory therapies in the initial stages of dementia may have potential benefits.

Temporal change in multimorbidity prevalence, clustering patterns, and the association with mortality: findings from the China Kadoorie Biobank study in Jiangsu Province.

Objectives: The characteristics of multimorbidity in the Chinese population are currently unclear. We aimed to determine the temporal change in multimorbidity prevalence, clustering patterns, and the association of multimorbidity with mortality from all causes and four major chronic diseases. Methods: This study analyzed data from the China Kadoorie Biobank study performed in Wuzhong District, Jiangsu Province. A total of 53,269 participants aged 30-79 years were recruited between 2004 and 2008. New diagnoses of 15 chronic diseases and death events were collected during the mean follow-up of 10.9 years. Yule's Q cluster analysis method was used to determine the clustering patterns of multimorbidity. A Cox proportional hazards model was used to estimate the associations of multimorbidity with mortalities. Results: The overall multimorbidity prevalence rate was 21.1% at baseline and 27.7% at the end of follow-up. Multimorbidity increased more rapidly during the follow-up in individuals who had a higher risk at baseline. Three main multimorbidity patterns were identified: (i) cardiometabolic multimorbidity (diabetes, coronary heart disease, stroke, and hypertension), (ii) respiratory multimorbidity (tuberculosis, asthma, and chronic obstructive pulmonary disease), and (iii) mental, kidney and arthritis multimorbidity (neurasthenia, psychiatric disorders, chronic kidney disease, and rheumatoid arthritis). There were 3,433 deaths during the follow-up. The mortality risk increased by 24% with each additional disease [hazard ratio (HR) = 1.24, 95% confidence interval (CI) = 1.20-1.29]. Compared with those without multimorbidity at baseline, both cardiometabolic multimorbidity and respiratory multimorbidity were associated with increased mortality from all causes and four major chronic diseases. Cardiometabolic multimorbidity was additionally associated with mortality from cardiovascular diseases and diabetes, with HRs of 2.64 (95% CI = 2.19-3.19) and 28.19 (95% CI = 14.85-53.51), respectively. Respiratory multimorbidity was associated with respiratory disease mortality, with an HR of 9.76 (95% CI = 6.22-15.31). Conclusion: The prevalence of multimorbidity has increased substantially over the past decade. This study has revealed that cardiometabolic multimorbidity and respiratory multimorbidity have significantly increased mortality rates. These findings indicate the need to consider high-risk populations and to provide local evidence for intervention strategies and health management in economically developed regions.

Common conditions of use elements. Atomic concepts for consistent and effective information governance.

Myriad policy, ethical and legal considerations underpin the sharing of biological resources, implying the need for standardised and yet flexible ways to digitally represent diverse 'use conditions'. We report a core lexicon of terms that are atomic, non-directional 'concepts of use', called Common Conditions of use Elements. This work engaged biobanks and registries relevant to the European Joint Programme for Rare Diseases and aimed to produce a lexicon that would have generalised utility. Seventy-six concepts were initially identified from diverse real-world settings, and via iterative rounds of deliberation and user-testing these were optimised and condensed down to 20 items. To validate utility, support software and training information was provided to biobanks and registries who were asked to create Sharing Policy Profiles. This succeeded and involved adding standardised directionality and scope annotations to the employed terms. The addition of free-text parameters was also explored. The approach is now being adopted by several real-world projects, enabling this standard to evolve progressively into a universal basis for representing and managing conditions of use.

Association between household size and risk of incident dementia in the UK Biobank study.

Currently, the relationship between household size and incident dementia, along with the underlying neurobiological mechanisms, remains unclear. This prospective cohort study was based on UK Biobank participants aged ≥ 50 years without a history of dementia. The linear and non-linear longitudinal association was assessed using Cox proportional hazards regression and restricted cubic spline models. Additionally, the potential mechanisms driven by brain structures were investigated by linear regression models. We included 275,629 participants (mean age at baseline 60.45 years [SD 5.39]). Over a mean follow-up of 9.5 years, 6031 individuals developed all-cause dementia. Multivariable analyses revealed that smaller household size was associated with an increased risk of all-cause dementia (HR, 1.06; 95% CI 1.02-1.09), vascular dementia (HR, 1.08; 95% CI 1.01-1.15), and non-Alzheimer's disease non-vascular dementia (HR, 1.09; 95% CI 1.03-1.14). No significant association was observed for Alzheimer's disease. Restricted cubic splines demonstrated a reversed J-shaped relationship between household size and all-cause and cause-specific dementia. Additionally, substantial associations existed between household size and brain structures. Our findings suggest that small household size is a risk factor for dementia. Additionally, brain structural differences related to household size support these associations. Household size may thus be a potential modifiable risk factor for dementia.

Identifying proteomic risk factors for cancer using prospective and exome analyses of 1463 circulating proteins and risk of 19 cancers in the UK Biobank.

The availability of protein measurements and whole exome sequence data in the UK Biobank enables investigation of potential observational and genetic protein-cancer risk associations. We investigated associations of 1463 plasma proteins with incidence of 19 cancers and 9 cancer subsites in UK Biobank participants (average 12 years follow-up). Emerging protein-cancer associations were further explored using two genetic approaches, cis-pQTL and exome-wide protein genetic scores (exGS). We identify 618 protein-cancer associations, of which 107 persist for cases diagnosed more than seven years after blood draw, 29 of 618 were associated in genetic analyses, and four had support from long time-to-diagnosis ( > 7 years) and both cis-pQTL and exGS analyses: CD74 and TNFRSF1B with NHL, ADAM8 with leukemia, and SFTPA2 with lung cancer. We present multiple blood protein-cancer risk associations, including many detectable more than seven years before cancer diagnosis and that had concordant evidence from genetic analyses, suggesting a possible role in cancer development.