Biobank Participants Research Articles

SLC10A1 rs2296651 variant (S267F mutation) predicts biochemical traits, hepatitis B virus infection susceptibility and the risk of gallstone disease.

Sodium taurocholate co-transporting polypeptide (NTCP), a bile acid transporter, plays a crucial role in regulating bile acid levels and influencing the risk of HBV infection. Genetic variations in the SLC10A1 gene, which encodes NTCP, affect these functions. However, the impact of SLC10A1 gene variants on the metabolic and biochemical traits remained unclear. We aimed to investigate the association of SLC10A1 gene variants with the clinical and biochemical parameters, and the risk of different HBV infection statuses and gallstone disease in the Taiwanese population. Genotyping data from 117,679 Taiwan Biobank participants were analyzed using the Axiom genome-wide CHB arrays. Regional-plot association analysis demonstrated genome-wide significant association between the SLC10A1 rs2296651 genotypes and lipid profile, gamma glutamyl transferase (γGT) level and anti-HBc-positivity. Genotype-phenotype association analyses revealed significantly lower total cholesterol, low-density lipoprotein (LDL) cholesterol and uric acid levels, a higher γGT level and a higher gallstone incidence in rare rs2296651-A allele carrier. Participants with the rs2296651 AA-genotype exhibited significantly lower rates of anti-HBc-positivity and HBsAg-positivity. Compared to those with the GG-genotype, individuals with non-GG-genotypes had reduced risks for various HBV infection statuses: the AA-genotype showed substantially lower risks, while the GA-genotype demonstrated modestly lower risks. Predictive tools also suggested that the rs2296651 variant potentially induced protein damage and pathogenic effects. In conclusion, our data revealed pleiotropic effects of the SLC10A1 rs2296651 genotypes on the levels of biochemical traits and the risk of HBV infection and gallstone disease. This confirms SLC10A1's versatility and implicates its genotypes in predicting both biochemical traits and disease susceptibility.

The risk of Alzheimer's disease and cognitive impairment characteristics in eight mental disorders: A UK Biobank observational study and Mendelian randomization analysis.

The cognitive impairment patterns and the association with Alzheimer's disease (AD) in mental disorders remain poorly understood. We analyzed data from 486,297 UK Biobank participants, categorizing them by mental disorder history to identify the risk of AD and the cognitive impairment characteristics. Causation was further assessed using Mendelian randomization (MR). AD risk was higher in individuals with bipolar disorder (BD; hazard ratio [HR]=2.37, P<0.01) and major depressive disorder (MDD; HR=1.63, P<0.001). MR confirmed a causal link between BD and AD (ORIVW=1.098), as well as obsessive-compulsive disorder (OCD) and AD (ORIVW=1.050). Cognitive impairments varied, with BD and schizophrenia showing widespread deficits, and OCD affecting complex task performance. Observational study and MR provide consistent evidence that mental disorders are independent risk factors for AD. Mental disorders exhibit distinct cognitive impairment prior to dementia, indicating the potential different mechanisms in AD pathogenesis. Early detection of these impairments in mental disorders is crucial for AD prevention. This is the most comprehensive study that investigates the risk and causal relationships between a history of mental disorders and the development of Alzheimer's disease (AD), alongside exploring the cognitive impairment characteristics associated with different mental disorders. Individuals with bipolar disorder (BD) exhibited the highest risk of developing AD (hazard ratio [HR]=2.37, P<0.01), followed by those with major depressive disorder (MDD; HR=1.63, P<0.001). Individuals with schizophrenia (SCZ) showed a borderline higher risk of AD (HR=2.36, P=0.056). Two-sample Mendelian randomization (MR) confirmed a causal association between BD and AD (ORIVW=1.098, P<0.05), as well as AD family history (proxy-AD, ORIVW=1.098, P<0.001), and kept significant after false discovery rate correction. MR also identified a nominal significant causal relationship between the obsessive-compulsive disorder (OCD) spectrum and AD (ORIVW=1.050, P<0.05). Individuals with SCZ, BD, and MDD exhibited impairments in multiple cognitive domains with distinct patterns, whereas those with OCD showed only slight declines in complex tasks.

Dietary pattern modifies the risk of MASLD through metabolomic signature

Background & AimsThe EAT-Lancet Commission in 2019 advocated a plant-centric diet for health and environmental benefits, but its relation to metabolic dysfunction-associated steatotic liver disease (MASLD) is unclear. We aimed to discover the metabolite profile linked to the EAT-Lancet diet and its association with MASLD risk, considering genetic predisposition. MethodsWe analyzed data from 105,752 UK Biobank participants with detailed dietary and metabolomic information. We constructed an EAT-Lancet diet index and derived a corresponding metabolomic signature through elastic net regression. A weighted polygenic risk score for MASLD was computed from associated risk variants. The Cox proportional hazards model was employed to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the risk of MASLD (defined as hospital admission or death). ResultsDuring a median follow-up period of 11.6 years, 1,138 cases of MASLD were documented. The multivariable HR (95% CI) of MASLD for the highest versus the lowest group for the EAT-Lancet diet index was 0.79 (0.66, 0.95). The diet's impact was unaffected by genetic predisposition to MASLD (P = 0.42). Moreover, a robust correlation was found between the metabolomic signature and the EAT-Lancet diet index (Pearson r = 0.29; P <0.0001). Participants with the highest group for the metabolomic signature showing a multivariable HR (95% CI) of 0.46 (0.37, 0.58) for MASLD, in comparison to those with the lowest group. ConclusionsHigher intake of the EAT-Lancet diet and its associated metabolite signature are both linked to a reduced risk of MASLD, independently of traditional risk factors. Impact and implicationsOur analysis leveraging the UK Biobank study showed higher adherence to the EAT-Lancet diet was associated with a reduced risk of MASLD. We identified a unique metabolite signature comprising 81 metabolites associated with the EAT-Lancet diet, potentially underlying the diet's protective mechanism against MASLD. These findings suggest the EAT-Lancet diet may offer substantial protective benefits against MASLD.

Implications of food ultra-processing on cardiovascular risk considering plant origin foods: an analysis of the UK Biobank cohort

Comprehensive research evidence is lacking on the role of ultra-processed foods (UPF) in the relationship between the consumption of plant-sourced foods and their impact on cardiovascular disease (CVD) outcomes. This study aims to assess CVD risk associated with the dietary contribution of food groups that consider both plant or animal origin and food processing categories, within a large cohort of British adults. Data from the UK Biobank participants (40-69y) who completed at least two 24-h dietary recalls between 2009 and 2012 (n=126,842; median follow-up: 9y), with subsequent data linkage to hospital and mortality records, were used. Food groups were classified as either plant-sourced or non-plant/animal-sourced foods. These groups were further divided into non-UPF and UPF, and expressed as a percentage of total energy intake. Every 10 percentage points increase in plant-sourced non-UPF consumption was associated with a 7% lower risk of CVD (95% CI 0.91-0.95) and a 13% lower risk of CVD mortality (0.80-0.94). Conversely, plant-sourced UPF consumption was associated with a 5% increased risk (1.03-1.07) and a 12% higher mortality (1.05-1.20). The contribution of all UPF was linked to higher CVD risk and mortality, and no evidence for an association between contribution of all plant-sourced foods and CVD incidence and mortality was observed. The dietary contribution of plant-sourced non-UPF inversely linked to CVD risk, while plant-sourced UPF contribution showed a positive association. Recognizing the role of food processing is crucial for favourable CVD outcomes, even in plant-sourced diets. World Cancer Research Fund.

Development and external validation of a head and neck cancer risk prediction model.

Head and neck cancer (HNC) incidence is on the rise, often diagnosed at late stage and associated with poor prognoses. Risk prediction tools have a potential role in prevention and early detection. The IARC-ARCAGE European case-control study was used as the model development dataset. A clinical HNC risk prediction model using behavioral and demographic predictors was developed via multivariable logistic regression analyses. The model was then externally validated in the UK Biobank cohort. Model performance was tested using discrimination and calibration metrics. 1926 HNC cases and 2043 controls were used for the development of the model. The development dataset model including sociodemographic, smoking, and alcohol variables had moderate discrimination, with an area under curve (AUC) value of 0.75 (95% CI, 0.74-0.77); the calibration slope (0.75) and tests were suggestive of good calibration. 384 616 UK Biobank participants (with 1177 HNC cases) were available for external validation of the model. Upon external validation, the model had an AUC of 0.62 (95% CI, 0.61-0.64). We developed and externally validated a HNC risk prediction model using the ARCAGE and UK Biobank studies, respectively. This model had moderate performance in the development population and acceptable performance in the validation dataset. Demographics and risk behaviors are strong predictors of HNC, and this model may be a helpful tool in primary dental care settings to promote prevention and determine recall intervals for dental examination. Future addition of HPV serology or genetic factors could further enhance individual risk prediction.

MSGene: a multistate model using genetic risk and the electronic health record applied to lifetime risk of coronary artery disease

Coronary artery disease (CAD) is the leading cause of death among adults worldwide. Accurate risk stratification can support optimal lifetime prevention. Current methods lack the ability to incorporate new information throughout the life course or to combine innate genetic risk factors with acquired lifetime risk. We designed a general multistate model (MSGene) to estimate age-specific transitions across 10 cardiometabolic states, dependent on clinical covariates and a CAD polygenic risk score. This model is designed to handle longitudinal data over the lifetime to address this unmet need and support clinical decision-making. We analyze longitudinal data from 480,638 UK Biobank participants and compared predicted lifetime risk with the 30-year Framingham risk score. MSGene improves discrimination (C-index 0.71 vs 0.66), age of high-risk detection (C-index 0.73 vs 0.52), and overall prediction (RMSE 1.1% vs 10.9%), in held-out data. We also use MSGene to refine estimates of lifetime absolute risk reduction from statin initiation. Our findings underscore our multistate model’s potential public health value for accurate lifetime CAD risk estimation using clinical factors and increasingly available genetics toward earlier more effective prevention.

Hippocampal volumes in UK Biobank are associated with APOE only in older adults.

The hippocampus atrophies with age and is implicated in neurodegenerative disorders including Alzheimer's disease (AD). We examined the interplay between age and APOE genotype on total hippocampal volume. Utilizing neuroimaging data from 37,463 UK Biobank participants, we applied linear regression to quantify the association of age and APOE with hippocampal volume and identified the age when volumes of ε2/ε3, ε3/ε4, and ε4/ε4 carriers significantly deviated from ε3/ε3 using generalized additive modeling. Total hippocampal volume declined with age, with significant differences by APOE genotype emerging after age 60. ε3/ε4 and ε4/ε4 carriers displayed reduced volumes from ages 69 and 61, respectively, while ε2/ε3 showed delayed decline starting at age 76. The association of APOE and hippocampal volume is age-dependent, with differences in volumes of ε4/ε4 carriers detected as early as age 61. This work underscores the importance of APOE genotype in determining when to begin screening for AD.

Personal light exposure patterns and incidence of type 2 diabetes: analysis of 13 million hours of light sensor data and 670,000 person-years of prospective observation

Light at night disrupts circadian rhythms, and circadian disruption is a risk factor for type 2 diabetes. Whether personal light exposure predicts diabetes risk has not been demonstrated in a large prospective cohort. We therefore assessed whether personal light exposure patterns predicted risk of incident type 2 diabetes in UK Biobank participants, using ∼13 million hours of light sensor data. Participants (N=84,790, age (M ± SD)=62.3±7.9 years, 58% female) wore light sensors for one week, recording day and night light exposure. Circadian amplitude and phase were modeled from weekly light data. Incident type 2 diabetes was recorded (1997 cases; 7.9±1.2 years follow-up; excluding diabetes cases prior to light-tracking). Risk of incident type 2 diabetes was assessed as a function of day and night light, circadian phase, and circadian amplitude, adjusting for age, sex, ethnicity, socioeconomic and lifestyle factors, and polygenic risk. Compared to people with dark nights (0-50th percentiles), diabetes risk was incrementally higher across brighter night light exposure percentiles (50-70th: multivariable-adjusted HR=1.29 [1.14-1.46]; 70-90th: 1.39 [1.24-1.57]; and 90-100th: 1.53 [1.32-1.77]). Diabetes risk was higher in people with lower modeled circadian amplitude (aHR=1.07 [1.03-1.10] per SD), and with early or late circadian phase (aHR range: 1.06-1.26). Nightlight and polygenic risk independently predicted higher diabetes risk. The difference in diabetes risk between people with bright and dark nights was similar to the difference between people with low and moderate genetic risk. Type 2 diabetes risk was higher in people exposed to brighter night light, and in people exposed to light patterns that may disrupt circadian rhythms. Avoidance of light at night could be a simple and cost-effective recommendation that mitigates risk of diabetes, even in those with high genetic risk. Australian Government Research Training Program.

Genetic Architecture and Clinical Outcomes of Combined Lipid Disturbances.

Dyslipoproteinemia often involves simultaneous derangements of multiple lipid traits. We aimed to evaluate the phenotypic and genetic characteristics of combined lipid disturbances in a general population-based cohort. Among UK Biobank participants without prevalent coronary artery disease, we used blood lipid and apolipoprotein B concentrations to ascribe individuals into 1 of 6 reproducible and mutually exclusive dyslipoproteinemia subtypes. Incident coronary artery disease risk was estimated for each subtype using Cox proportional hazards models. Phenome-wide analyses and genome-wide association studies were performed for each subtype, followed by in silico causal gene prioritization and heritability analyses. Additionally, the prevalence of disruptive variants in causal genes for Mendelian lipid disorders was assessed using whole-exome sequence data. Among 450 636 UK Biobank participants: 63 (0.01%) had chylomicronemia; 40 005 (8.9%) had hypercholesterolemia; 94 785 (21.0%) had combined hyperlipidemia; 13 998 (3.1%) had remnant hypercholesterolemia; 110 389 (24.5%) had hypertriglyceridemia; and 49 (0.01%) had mixed hypertriglyceridemia and hypercholesterolemia. Over a median (interquartile range) follow-up of 11.1 (10.4-11.8) years, incident coronary artery disease risk varied across subtypes, with combined hyperlipidemia exhibiting the largest hazard (hazard ratio, 1.92 [95% CI, 1.84-2.01]; P=2×10-16), even when accounting for non-HDL-C (hazard ratio, 1.45 [95% CI, 1.30-1.60]; P=2.6×10-12). Genome-wide association studies revealed 250 loci significantly associated with dyslipoproteinemia subtypes, of which 72 (28.8%) were not detected in prior single lipid trait genome-wide association studies. Mendelian lipid variant carriers were rare (2.0%) among individuals with dyslipoproteinemia, but polygenic heritability was high, ranging from 23% for remnant hypercholesterolemia to 54% for combined hyperlipidemia. Simultaneous assessment of multiple lipid derangements revealed nuanced differences in coronary artery disease risk and genetic architectures across dyslipoproteinemia subtypes. These findings highlight the importance of looking beyond single lipid traits to better understand combined lipid and lipoprotein phenotypes and implications for disease risk.

Gene-environment interactions between clonal hematopoiesis of indeterminate potential and air pollution in non-small cell lung cancer among non-smokers.

10514 Background: Small particulate matter air pollution (≤ 2.5µm diameter; PM2.5) is a recognized driver of non-small cell lung cancer (NSCLC) among non-smokers. PM2.5 recruits pro-inflammatory macrophages to the lungs, which facilitate the clonal expansion of mutated epithelial cells and eventual transformation to NSCLC. Clonal hematopoiesis of indeterminate potential (CHIP) is a common age-related condition caused by the acquisition of somatic mutations in hematopoietic stem cells. CHIP and its accompanying pro-inflammatory phenotype have been linked with various age-related diseases, including incident NSCLC; however, the mechanisms underlying this relationship are unknown. In this study, we aimed to explore the interaction between CHIP and exposure to PM2.5 in the development of incident NSCLC. Methods: This study was conducted using data from participants in the UK Biobank (n = 451,095). CHIP status was determined from peripheral blood whole exome sequencing data, and defined as the presence of a somatic driver mutation in the blood at variant allele frequency (VAF) ≥2% (PMID: 36652671). Incident NSCLC was determined from UK cancer registry data, and PM2.5 exposure was determined based on ambient regional measures from 2010. Cox proportional hazard models were used to evaluate associations between CHIP, PM2.5, and NSCLC. Proteomics data was measured using OLINK proteomics in a subset of UK Biobank participants (n = 44,625). Results: CHIP was prevalent in 3.4% of UK Biobank participants (n = 15,633; never smokers: 3.0%, n = 6,916/227,133). There were 1983 incident cases of NSCLC (never smokers: n = 307). CHIP status was associated with incident NSCLC when adjusting for smoking status (HR = 1.73, 95% CI: 1.48–2.02) and analyzing exclusively non-smokers (HR = 2.01, 95% CI: 1.34-3.00). PM2.5 levels were not associated with NSCLC in non-smokers (HR = 1.00, 95% CI: 0.89–1.12 per µg/m3 increase in PM2.5); however, there was a significant interaction between PM2.5 and CHIP (HR = 1.46, 95% CI: 1.02–2.11, pint = 0.04), suggesting that it is the interplay between the two that drives incident NSCLC risk. We found no association between PM2.5 levels and increased CHIP prevalence or CHIP VAF. PM2.5 and CHIP were also found to interact to increase systemic inflammatory markers C-reactive peptide (pint = 0.01) and IL-6 (pint = 0.002). Conclusions: PM2.5 and CHIP act as a novel gene x environment interaction pair that play a key role in NSCLC etiology among non-smokers. Rather than acting in isolation to increase risk of NSCLC, PM2.5 intensifies the relationship between CHIP and NSCLC, presumably by exacerbating systemic inflammation and the hyper-inflammatory lung microenvironment. With PM2.5 levels in the UK among the lowest in the world, we posit that the CHIP x PM2.5 interaction contributes substantially to the global burden of NSCLC in non-smokers.

Association of Domestic Water Hardness with All-Cause and Cause-Specific Cancers: Evidence from 447,996 UK Biobank Participants.

Accumulating evidence suggests that domestic water hardness is linked to health outcomes, but its association to all-cause and cause-specific cancers warrants investigation. The aim of this study was to investigate the association of domestic hard water with all-cause and cause-specific cancers. In the prospective cohort study, a total of 447,996 participants from UK Biobank who were free of cancer at baseline were included and followed up for 16 y. All-cause and 22 common cause-specific cancer diagnoses were ascertained using hospital inpatient records and self-reported data until 30 November 2022. Domestic water hardness, measured by concentrations, was obtained from the local water supply companies across England, Scotland, and Wales in 2005. Data were analyzed using Cox proportional hazard models, with adjustments for known measured confounders, including demographic, socioeconomic, clinical, biochemical, lifestyle, and environmental factors. Over a median follow-up of 13.6 y (range: 12.7-14.4 y), 58,028 all-cause cancer events were documented. A U-shaped relationship between domestic water hardness and all-cause cancers was observed ( for nonlinearity ). In comparison with individuals exposed to soft water (), the hazard ratios (HRs) and 95% confidence intervals (CIs) of all-cause cancer were 1.00 (95% CI: 0.98, 1.02) for those exposed to moderate hard water (), 0.88 (95% CI: 0.84, 0.91) for those exposed to hard water () and 1.06 (95% CI: 1.04, 1.08) for those exposed to very hard water (). Additionally, domestic water hardness was associated with 11 of 22 cause-specific cancers, including cancers of the esophagus, stomach, colorectal tract, lung, breast, prostate, and bladder, as well as non-Hodgkin lymphoma, multiple myeloma, malignant melanoma, and hematological malignancies. Moreover, we observed a positive linear relationship between water hardness and bladder cancer. Our findings suggest that domestic water hardness was associated with all-cause and multiple cause-specific cancers. Findings from the UK Biobank support a potentially beneficial association between hard water and the incidence of all-cause cancer. However, very hard water may increase the risk of all-cause cancer. https://doi.org/10.1289/EHP13606.

Comorbidity Profiles of Posttraumatic Stress Disorder Across the Medical Phenome

BackgroundPrevious epidemiological research has linked posttraumatic stress disorder (PTSD) with specific physical health problems, but the comprehensive landscape of medical conditions associated with PTSD remains uncharacterized. Electronic health records provide an opportunity to overcome clinical knowledge gaps and uncover associations with biological relevance that potentially vary by sex. MethodsPTSD was defined among biobank participants (N = 145,959) in 3 major healthcare systems using 2 ICD code-based definitions: broad (≥1 PTSD or acute stress codes vs. 0; ncases = 16,706) and narrow (≥2 PTSD codes vs. 0; ncases = 3325). Using a phenome-wide association study design, we tested associations between each PTSD definition and all prevalent disease umbrella categories, i.e., phecodes. We also conducted sex-stratified phenome-wide association study analyses including a sex × diagnosis interaction term in each logistic regression. ResultsA substantial number of phecodes were significantly associated with PTSDNarrow (61%) and PTSDBroad (83%). While the strongest associations were shared between the 2 definitions, PTSDBroad captured 334 additional phecodes not significantly associated with PTSDNarrow and exhibited a wider range of significantly associated phecodes across various categories, including respiratory, genitourinary, and circulatory conditions. Sex differences were observed in that PTSDBroad was more strongly associated with osteoporosis, respiratory failure, hemorrhage, and pulmonary heart disease among male patients and with urinary tract infection, acute pharyngitis, respiratory infections, and overweight among female patients. ConclusionsThis study provides valuable insights into a diverse range of comorbidities associated with PTSD, including both known and novel associations, while highlighting the influence of sex differences and the impact of defining PTSD using electronic health records.

Mediating and moderating effects of plasma proteomic biomarkers on the association between poor oral health problems and incident dementia: The UK Biobank study.

The plasma proteome can mediate poor oral health problems (POHP)'s link to incident dementia. We screened 37,269 UK Biobank participants 50-74years old(2006-2010) for prevalent POHP, further tested against 1463 plasma proteins and incident dementia over up to 15years of follow-up. Total effect (TE) of POHP-dementia through plasma proteomic markers was decomposed into pure indirect effect (PIE), interaction referent (INTREF), controlled direct effect (CDE), or mediated interaction (INTMED). POHP increased the risk of all-cause dementia by 17% (P < 0.05). Growth differentiation factor 15 (GDF15) exhibited the strongest mediating effects (PIE > 0, P < 0.001), explaining 28% the total effect of POHP on dementia, as a pure indirect effect. A first principal component encompassing top 4 mediators (GDF15, IL19, MMP12, and ACVRL1), explained 11% of the POHP-dementia effect as a pure indirect effect. Pathway analysis including all mediators (k = 173 plasma proteins) revealed the involvement of the immune system, signal transduction, metabolism, disease, and gene expression, while STRING analysis indicated that top mediators within the first principal component were also represented in the two largest proteomic clusters. The dominant biological GO pathway for the GDF15 cluster was GO:0007169 labeled as "transmembrane receptor protein tyrosine kinase signaling pathway." Dementia is linked to POHP mediated by GDF15 among several proteomic markers.

Specification curve analysis to identify heterogeneity in risk factors for dementia: findings from the UK Biobank

BackgroundIn 2020, the Lancet Commission identified 12 risk factors as priorities for prevention of dementia, and other studies identified APOE e4/e4 genotype and family history of Alzheimer’s disease strongly associated with dementia outcomes; however, it is unclear how robust these relationships are across dementia subtypes and analytic scenarios. Specification curve analysis (SCA) is a new tool to probe how plausible analytical scenarios influence outcomes.MethodsWe evaluated the heterogeneity of odds ratios for 12 risk factors reported from the Lancet 2020 report and two additional strong associated non-modifiable factors (APOE e4/e4 genotype and family history of Alzheimer’s disease) with dementia outcomes across 450,707 UK Biobank participants using SCA with 5357 specifications across dementia subtypes (outcomes) and analytic models (e.g., standard demographic covariates such as age or sex and/or 14 correlated risk factors).ResultsSCA revealed variable dementia risks by subtype and age, with associations for TBI and APOE e4/e4 robust to model specification; in contrast, diabetes showed fluctuating links with dementia subtypes. We found that unattributed dementia participants had similar risk factor profiles to participants with defined subtypes.ConclusionsWe observed heterogeneity in the risk of dementia, and estimates of risk were influenced by the inclusion of a combination of other modifiable risk factors; non-modifiable demographic factors had a minimal role in analytic heterogeneity. Future studies should report multiple plausible analytic scenarios to test the robustness of their association. Considering these combinations of risk factors could be advantageous for the clinical development and evaluation of novel screening models for different types of dementia.

Noninvasive assessment of organ-specific and shared pathways in multi-organ fibrosis using T1 mapping.

Fibrotic diseases affect multiple organs and are associated with morbidity and mortality. To examine organ-specific and shared biologic mechanisms that underlie fibrosis in different organs, we developed machine learning models to quantify T1 time, a marker of interstitial fibrosis, in the liver, pancreas, heart and kidney among 43,881 UK Biobank participants who underwent magnetic resonance imaging. In phenome-wide association analyses, we demonstrate the association of increased organ-specific T1 time, reflecting increased interstitial fibrosis, with prevalent diseases across multiple organ systems. In genome-wide association analyses, we identified 27, 18, 11 and 10 independent genetic loci associated with liver, pancreas, myocardial and renal cortex T1 time, respectively. There was a modest genetic correlation between the examined organs. Several loci overlapped across the examined organs implicating genes involved in a myriad of biologic pathways including metal ion transport (SLC39A8, HFE and TMPRSS6), glucose metabolism (PCK2), blood group antigens (ABO and FUT2), immune function (BANK1 and PPP3CA), inflammation (NFKB1) and mitosis (CENPE). Finally, we found that an increasing number of organs with T1 time falling in the top quintile was associated with increased mortality in the population. Individuals with a high burden of fibrosis in ≥3 organs had a 3-fold increase in mortality compared to those with a low burden of fibrosis across all examined organs in multivariable-adjusted analysis (hazard ratio = 3.31, 95% confidence interval 1.77-6.19; P = 1.78 × 10-4). By leveraging machine learning to quantify T1 time across multiple organs at scale, we uncovered new organ-specific and shared biologic pathways underlying fibrosis that may provide therapeutic targets.

Systems biology dissection of PTSD and MDD across brain regions, cell types, and blood.

The molecular pathology of stress-related disorders remains elusive. Our brain multiregion, multiomic study of posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) included the central nucleus of the amygdala, hippocampal dentate gyrus, and medial prefrontal cortex (mPFC). Genes and exons within the mPFC carried most disease signals replicated across two independent cohorts. Pathways pointed to immune function, neuronal and synaptic regulation, and stress hormones. Multiomic factor and gene network analyses provided the underlying genomic structure. Single nucleus RNA sequencing in dorsolateral PFC revealed dysregulated (stress-related) signals in neuronal and non-neuronal cell types. Analyses of brain-blood intersections in >50,000 UK Biobank participants were conducted along with fine-mapping of the results of PTSD and MDD genome-wide association studies to distinguish risk from disease processes. Our data suggest shared and distinct molecular pathology in both disorders and propose potential therapeutic targets and biomarkers.

Association of leukocyte telomere length with cardiac conduction disease and sick sinus syndrome

Abstract Background Cardiac conduction disease (CCD) and sick sinus syndrome (SSS) may be related to a degenerative process. Leukocyte telomere length (LTL) is associated with the aging process and age-related degenerative diseases. We aimed to investigate the association between LTL and the risks of CCD/SS, and to explore whether LTL is related with cardiovascular imaging and electrocardiographic (ECG) changes. Methods This is a population-based cross-sectional study of UK Biobank participants without history of CCD/SSS recruited from 2006 to 2010. LTL was measured using a quantitative polymerase chain reaction method. Cardiovascular measurements were derived from cardiovascular magnetic resonance using machine learning. The median (IQR) duration of follow-up was 12.0 (11.3-12.7) years. The associations of LTL with imaging and ECG measurements and incident CCD/SSS were evaluated by multivariable regression models. Results Among the 412,452 white participants, 188,891 (45.8%) were male, with a mean age of 57.3 years. Longer LTL was independently associated with positive cardiac remodeling, including higher left ventricular mass, larger atrial volume, and increased atrial stroke volumes. However, no significant associations were observed with ECG findings including PR interval and P-wave duration. 11991 (2.6%) participants developed CCD and 984 (0.2%) developed SSS. Longer LTL was not associated with younger age. However, longer LTL was not associated with a lower risk of incident CCD (LTL fourth quartile vs. first quartile: hazard ratio, 0.98; 95% CI, 0.97-1.0; P = 0.057) or SSS (LTL fourth quartile vs. first quartile: hazard ratio, 0.98; 95% CI, 0.92-1.05; P = 0.554). Conclusions In this cross-sectional study, longer LTL was associated with a larger atrial size with better atrial function in middle age, but not with ECG changes. However, longer LTL was not associated with a lower risk of incident CCD and SSS.

#840 Kidney cancer, treatment with nephrectomy and survival in chronic kidney disease (CKD)

Abstract Background and Aims People with chronic kidney disease (CKD) have increased incidence of kidney cancer and poorer survival post-diagnosis compared to people without CKD. Nephrectomy, either partial or radical is the primary treatment for many kidney cancers and can be curative even in cases with locally advanced disease or single metastasis. We hypothesised that nephrectomy may be less frequently undertaken in people with kidney cancer and pre-existing CKD and that this might contribute to poorer survival in this group. Method Using data from the prospective research cohort UK Biobank (n = 502,536) linked to cancer registry, participants with available biochemistry and a new diagnosis of kidney cancer during follow-up were identified. Occurrence of nephrectomy was extracted from linked hospital data and all-cause mortality data from death certification records. Estimated glomerular filtration rate (eGFRCr) was calculated by CKD-EPI 2009 formula with race coefficient, as this was the formula recommended for use in the UK at the time of recruitment to UK Biobank. Cox proportional hazards models tested associations between eGFRCr and i) undergoing nephrectomy and ii) all-cause mortality by 10 ml/min/1.73 m2 decline from a reference value of 90 ml/min/1.73 m2. We additionally conducted subgroup analyses for nephrectomy and all-cause mortality within eGFRCr categories &amp;gt;105, 90-105, 75-90 (reference), 60-75, 45-60, 30-45 and &amp;lt;30 ml/min/1.73 m2. Both models were adjusted for age, sex, diabetes mellitus, hypertension, stroke, ischaemic heart disease, body mass index and socioeconomic deprivation. The all-cause mortality model was additionally adjusted for undergoing nephrectomy. Results There were 2053 participants with a new diagnosis of kidney cancer and sufficient biochemical data for inclusion. Of these, 935 (46%) had eGFRCr 60-90 ml/min/1.73 m2 and 139 (7%) had eGFRCr &amp;lt;60 ml/min/1.73 m2. Median time from baseline to kidney cancer diagnosis was 5.8 (IQR 0.9, 8.8) years. Median follow-up time after a diagnosis of kidney cancer was 3.4 (IQR 0.9, 6.6) years. For each 10 ml/min/1.73 m2 decline in eGFRCr below 90 ml/min/1.73 m2, there was no significant difference in likelihood of receiving nephrectomy (HR 1.05, p = 0.08) and no significant difference in likelihood of all-cause mortality (HR 1.03, p = 0.23). People with moderate-advanced CKD had increased hazards of all-cause mortality compared to the reference group (eGFRCr 75-90 ml/min/1.73 m2) when models were run by eGFRCr category (eGFRCr 30-45—HR 1.9 95% CI 1.3-3.0; eGFRCr &amp;lt;30—HR 2.0 95% CI 1.0-4.0). Conclusion In UK Biobank participants with kidney cancer and mild CKD, there was no significant difference in likelihood of nephrectomy or in hazards of all-cause mortality associated with declining eGFRCr as a continuous variable. Moderate to advanced CKD (eGFR &amp;lt;45) was associated with increased all-cause mortality despite adjustment for nephrectomy, suggesting that this finding is not explained by reduced access to surgical treatment.

#1081 Associations of MRI-derived kidney volume, kidney function, body composition, and physical performance in &amp;gt;38 000 UK Biobank participants

Abstract Background and Aims Kidney volume is used as predictive and therapeutic marker for several clinical conditions. However, there is a lack of large-scale studies examining the relationship between kidney volume and various clinicodemographic factors, including kidney function, body composition, and physical performance. Method In this observational study, MRI-derived kidney volume measurements from 38,526 UK Biobank participants were analyzed. Major kidney volume-related measures included body surface area (BSA)-adjusted total kidney volume (TKV) and the difference of bilateral kidneys. Multivariable-adjusted linear regression and cubic spline analyses were used to explore the association between kidney volume-related measures and clinicodemographic factors. Cox regression was used to identify the risks of death, non-kidney cancer, myocardial infarction (MI), and ischemic stroke. Results The median of BSA-adjusted TKV and difference in kidney volume were 141.9 (128.1–156.9) mL/m2 and 1.08 (1.04–1.15) fold, respectively. Higher BSA-adjusted TKV was significantly associated with higher eGFR (beta [95% CIs], 0.43 [0.42–0.44]; P &amp;lt; 0.001), higher composition of muscle volume (beta [95% CIs], 0.50 [0.48–0.51]; P &amp;lt; 0.001), and higher mean handgrip strength (beta [95% CIs], 0.15 [0.13–0.16]; P &amp;lt; 0.001), while associated with lower visceral adipose tissue volume (VAT, beta [95% CIs], −0.09 [−0.11 – −0.07]; P &amp;lt; 0.001) in adjusted models. Higher difference in bilateral kidney volumes was associated with lower eGFR, muscle volume, and physical performance, while associated with higher proteinuria and VAT. Conclusion Higher BSA-adjusted TKV and lower discrepancies in bilateral kidney volumes are associated with higher renal function, muscle volume, and physical performance.

Association of physical activity pattern and risk of Parkinson’s disease

Increasing evidence suggests an association between exercise duration and Parkinson’s disease. However, no high-quality prospective evidence exists confirming whether differences exist between the two modes of exercise, weekend warrior and equal distribution of exercise duration, and Parkinson’s risk. Hence, this study aimed to explore the association between different exercise patterns and Parkinson’s risk using exercise data from the UK Biobank. The study analyzed data from 89,400 UK Biobank participants without Parkinson’s disease. Exercise data were collected using the Axivity AX3 wrist-worn triaxial accelerometer. Participants were categorized into three groups: inactive, regularly active, and engaged in the weekend warrior (WW) pattern. The relationship between these exercise patterns and Parkinson’s risk was assessed using a multifactorial Cox model. During a mean follow-up of 12.32 years, 329 individuals developed Parkinson’s disease. In a multifactorial Cox model, using the World Health Organization–recommended threshold of 150 min of moderate-to-vigorous physical activity per week, both the active WW group [hazard ratio (HR) = 0.58; 95% confidence interval (CI) = 0.43–0.78; P < 0.001] and the active regular group (HR = 0.44; 95% CI = 0.34–0.57; P < 0.001) exhibited a lower risk of developing Parkinson’s disease compared with the inactive group. Further, no statistically significant difference was observed between the active WW and the active regular groups (HR = 0.77; 95% CI = 0.56–1.05; P = 0.099). In conclusion, in this cohort study, both the WW exercise pattern and an equal distribution of exercise hours were equally effective in reducing Parkinson’s risk.