Insights into the genetic architecture of cerebellar lobules derived from the UK Biobank.

In this work we endeavor to further understand the genetic architecture of the cerebellum by examining the genetic underpinnings of the different cerebellar lob(ul)es, identifying their genetic relation to cortical and subcortical regions, as well as to psychiatric disorders, as well as traces of their evolutionary trajectories. We confirm the moderate heritability of cerebellar volumes, and reveal genetic clustering and variability across their different substructures, which warranted a detailed analysis using this higher structural resolution. We replicated known genetic correlations with several subcortical volumes, and report new cortico-cerebellar genetic correlations, including negative genetic correlations between anterior cerebellar lobules and cingulate, and positive ones between lateral Crus I and lobule VI with cortical measures in the fusiform region. Heritability partitioning for evolutionary annotations highlighted that the vermis of Crus II has depleted heritability in genomic regions of "archaic introgression deserts", but no enrichment/depletion of heritability in any other cerebellar regions. Taken together, these findings reveal novel insights into the genetic underpinnings of the different cerebellar lobules.

Polygenic risk score-based phenome-wide association for glaucoma and its impact on disease susceptibility in two large biobanks.

BACKGROUND: Glaucoma is a leading cause of worldwide irreversible blindness. Considerable uncertainty remains regarding the association between a variety of phenotypes and the genetic risk of glaucoma, as well as the impact they exert on the glaucoma development. METHODS: We investigated the associations of genetic liability for primary open angle glaucoma (POAG) with a wide range of potential risk factors and to assess its impact on the risk of incident glaucoma. The phenome-wide association study (PheWAS) approach was applied to determine the association of POAG polygenic risk score (PRS) with a wide range of phenotypes in 377, 852 participants from the UK Biobank study and 43,623 participants from the Penn Medicine Biobank study, all of European ancestry. Participants were stratified into four risk tiers: low, intermediate, high, and very high-risk. Cox proportional hazard models assessed the relationship of POAG PRS and ocular factors with new glaucoma events. RESULTS: In both discovery and replication set in the PheWAS, a higher genetic predisposition to POAG was specifically correlated with ocular disease phenotypes. The POAG PRS exhibited correlations with low corneal hysteresis, refractive error, and ocular hypertension, demonstrating a strong association with the onset of glaucoma. Individuals carrying a high genetic burden exhibited a 9.20-fold, 11.88-fold, and 28.85-fold increase in glaucoma incidence when associated with low corneal hysteresis, high myopia, and elevated intraocular pressure, respectively. CONCLUSION: Genetic susceptibility to POAG primarily influences ocular conditions, with limited systemic associations. Notably, the baseline polygenic risk for POAG robustly associates with new glaucoma events, revealing a large combined effect of genetic and ocular risk factors on glaucoma incidents.

Variability in the prevalence of depression among adults with chronic pain: UK Biobank analysis through clinical prediction models.

BACKGROUND: The prevalence of depression among people with chronic pain remains unclear due to the heterogeneity of study samples and definitions of depression. We aimed to identify sources of variation in the prevalence of depression among people with chronic pain and generate clinical prediction models to estimate the probability of depression among individuals with chronic pain. METHODS: Participants were from the UK Biobank. The primary outcome was a "lifetime" history of depression. The model's performance was evaluated using discrimination (optimism-corrected C statistic) and calibration (calibration plot). RESULTS: Analyses included 24,405 patients with chronic pain (mean age 64.1 years). Among participants with chronic widespread pain, the prevalence of having a "lifetime" history of depression was 45.7% and varied (25.0-66.7%) depending on patient characteristics. The final clinical prediction model (optimism-corrected C statistic: 0.66; good calibration on the calibration plot) included age, BMI, smoking status, physical activity, socioeconomic status, gender, history of asthma, history of heart failure, and history of peripheral artery disease. Among participants with chronic regional pain, the prevalence of having a "lifetime" history of depression was 30.2% and varied (21.4-70.6%) depending on patient characteristics. The final clinical prediction model (optimism-corrected C statistic: 0.65; good calibration on the calibration plot) included age, gender, nature of pain, smoking status, regular opioid use, history of asthma, pain location that bothers you most, and BMI. CONCLUSIONS: There was substantial variability in the prevalence of depression among patients with chronic pain. Clinically relevant factors were selected to develop prediction models. Clinicians can use these models to assess patients' treatment needs. These predictors are convenient to collect during daily practice, making it easy for busy clinicians to use them.

Predicting the risk of lung cancer using machine learning: A large study based on UK Biobank.

In response to the high incidence and poor prognosis of lung cancer, this study tends to develop a generalizable lung-cancer prediction model by using machine learning to define high-risk groups and realize the early identification and prevention of lung cancer. We included 467,888 participants from UK Biobank, using lung cancer incidence as an outcome variable, including 49 previously known high-risk factors and less studied or unstudied predictors. We developed multivariate prediction models using multiple machine learning models, namely logistic regression, naïve Bayes, random forest, and extreme gradient boosting models. The performance of the models was evaluated by calculating the areas under their receiver operating characteristic curves, Brier loss, log loss, precision, recall, and F1 scores. The Shapley additive explanations interpreter was used to visualize the models. Three were ultimately 4299 cases of lung cancer that were diagnosed in our sample. The model containing all the predictors had good predictive power, and the extreme gradient boosting model had the best performance with an area under curve of 0.998. New important predictive factors for lung cancer were also identified, namely hip circumference, waist circumference, number of cigarettes previously smoked daily, neuroticism score, age, and forced expiratory volume in 1 second. The predictive model established by incorporating novel predictive factors can be of value in the early identification of lung cancer. It may be helpful in stratifying individuals and selecting those at higher risk for inclusion in screening programs.

Influence of age and sex on longitudinal metabolic profiles and body weight trajectories in the UK Biobank.

BACKGROUND: Accurate characterization of how age influences body weight and metabolism at different stages of life is important for understanding ageing processes. Here, we explore observational longitudinal associations between metabolic health and weight from the fifth to the seventh decade of life, using carefully adjusted statistical designs. METHODS: Body measures and biochemical data from blood and urine (220 measures) across two visits were available from 10 104 UK Biobank participants. Participants were divided into stable (within ±4% per decade), weight loss and weight gain categories. Final subgroups were metabolically matched at baseline (48% women, follow-up 4.3 years, ages 41-70; n = 3368 per subgroup) and further stratified by the median age of 59.3 years and sex. RESULTS: Pulse pressure, haemoglobin A1c and cystatin-C tracked ageing consistently (P < 0.0001). In women under 59, age-associated increases in citrate, pyruvate, alkaline phosphatase and calcium were observed along with adverse changes across lipoprotein measures, fatty acid species and liver enzymes (P < 0.0001). Principal component analysis revealed a qualitative sex difference in the temporal relationship between body weight and metabolism: weight loss was not associated with systemic metabolic improvement in women, whereas both age strata converged consistently towards beneficial (weight loss) or adverse (weight gain) phenotypes in men. CONCLUSIONS: We report longitudinal ageing trends for 220 metabolic measures in absolute concentrations, many of which have not been described for older individuals before. Our results also revealed a fundamental dynamic sex divergence that we speculate is caused by menopause-driven metabolic deterioration in women.

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Objective: To investigate the longitudinal association between alcohol abstinence and accelerated biological aging among middle-aged and older adults and to explore the potential effect modifiers influencing the association. Methods: Utilizing the clinico-biochemical and anthropometric data from the baseline and first repeat survey of the UK Biobank (UKB), we employed the Klemera and Doubal method (KDM) to construct the biological age (BA) and calculate BA acceleration. Change analysis based on multivariate linear regression models was employed to explore the association between changes in alcohol abstinence and changes in BA acceleration. Age, sex, smoking status, tea and coffee consumption, and body mass index were considered as the stratification factors for conducting stratified analysis. Results: A total of 5 412 participants were included. Short-term alcohol abstinence (ß=1.00, 95% confidence interval [CI]: 0.15-1.86) was found to accelerate biological aging when compared to consistent never drinking, while long-term abstinence (ß=-0.20, 95% CI: -1.12-0.71) did not result in a significant acceleration of biological aging. Body mass index may be a potential effect modifier. Conclusion: Short-term alcohol abstinence was associated with accelerated biological aging, but the effect gradually diminishes over extended periods of abstinence.

3Dmapper: a command line tool for BioBank-scale mapping of variants to protein structures.

MOTIVATION: The interpretation of genomic data is crucial to understand the molecular mechanisms of biological processes. Protein structures play a vital role in facilitating this interpretation by providing functional context to genetic coding variants. However, mapping genes to proteins is a tedious and error-prone task due to inconsistencies in data formats. Over the past two decades, numerous tools and databases have been developed to automatically map annotated positions and variants to protein structures. However, most of these tools are web-based and not well-suited for large-scale genomic data analysis. RESULTS: To address this issue, we introduce 3Dmapper, a stand-alone command-line tool developed in Python and R. It systematically maps annotated protein positions and variants to protein structures, providing a solution that is both efficient and reliable. AVAILABILITY AND IMPLEMENTATION: https://github.com/vicruiser/3Dmapper.

Left Ventricular Trabeculations at Cardiac MRI: Reference Ranges and Association with Cardiovascular Risk Factors in UK Biobank.

Background The extent of left ventricular (LV) trabeculation and its relationship with cardiovascular (CV) risk factors is unclear. Purpose To apply automated segmentation to UK Biobank cardiac MRI scans to (a) assess the association between individual characteristics and CV risk factors and trabeculated LV mass (LVM) and (b) establish normal reference ranges in a selected group of healthy UK Biobank participants. Materials and Methods In this cross-sectional secondary analysis, prospectively collected data from the UK Biobank (2006 to 2010) were retrospectively analyzed. Automated segmentation of trabeculations was performed using a deep learning algorithm. After excluding individuals with known CV diseases, White adults without CV risk factors (reference group) and those with preexisting CV risk factors (hypertension, hyperlipidemia, diabetes mellitus, or smoking) (exposed group) were compared. Multivariable regression models, adjusted for potential confounders (age, sex, and height), were fitted to evaluate the associations between individual characteristics and CV risk factors and trabeculated LVM. Results Of 43 038 participants (mean age, 64 years ± 8 [SD]; 22 360 women), 28 672 individuals (mean age, 66 years ± 7; 14 918 men) were included in the exposed group, and 7384 individuals (mean age, 60 years ± 7; 4729 women) were included in the reference group. Higher body mass index (BMI) (ß = 0.66 [95% CI: 0.63, 0.68]; P < .001), hypertension (ß = 0.42 [95% CI: 0.36, 0.48]; P < .001), and higher physical activity level (ß = 0.15 [95% CI: 0.12, 0.17]; P < .001) were associated with higher trabeculated LVM. In the reference group, the median trabeculated LVM was 6.3 g (IQR, 4.7-8.5 g) for men and 4.6 g (IQR, 3.4-6.0 g) for women. Median trabeculated LVM decreased with age for men from 6.5 g (IQR, 4.8-8.7 g) at age 45-50 years to 5.9 g (IQR, 4.3-7.8 g) at age 71-80 years (P = .03). Conclusion Higher trabeculated LVM was observed with hypertension, higher BMI, and higher physical activity level. Age- and sex-specific reference ranges of trabeculated LVM in a healthy middle-aged White population were established. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Kawel-Boehm in this issue.

The Association between Lifestyle Factors and COVID-19: Findings from Qatar Biobank.

Coronavirus Disease 2019 (COVID-19) manifestations range from mild to severe life-threatening symptoms, including death. COVID-19 susceptibility has been associated with various factors, but studies in Qatar are limited. The objective of this study was to investigate the correlation between COVID-19 susceptibility and various sociodemographic and lifestyle factors, including age, gender, body mass index, smoking status, education level, dietary patterns, supplement usage, physical activity, a history of bariatric surgery, diabetes, and hypertension. We utilized logistic regression to analyze these associations, using the data of 10,000 adult participants, aged from 18 to 79, from Qatar Biobank. In total, 10.5% (n = 1045) of the participants had COVID-19. Compared to non-smokers, current and ex-smokers had lower odds of having COVID-19 (odds ratio [OR] = 0.55; 95% CI: 0.44-0.68 and OR = 0.70; 95% CI: 0.57-0.86, respectively). Vitamin D supplement use was associated with an 18% reduction in the likelihood of contracting COVID-19 (OR = 0.82; 95% CI: 0.69-0.97). Obesity (BMI ≥ 30 kg/m2), a history of bariatric surgery, and higher adherence to the modern dietary pattern-characterized by the consumption of foods high in saturated fat and refined carbohydrates-were positively associated with COVID-19. Our findings indicate that adopting a healthy lifestyle may be helpful in the prevention of COVID-19 infection.

Assessment of new-onset heart failure prediction in a diabetic population using left ventricular global strain: a prospective cohort study based on UK Biobank.

Background: Impaired glucose utilization influences myocardial contractile function. However, the prognostic importance of left ventricular global radial strain (LV-GRS), left ventricular global circumferential strain (LV-GCS), and left ventricular global longitudinal strain (LV-GLS) in predicting new-onset heart failure (HF) in a population with diabetes is unclear. Methods: The study design is prospective cohort from the UK Biobank. Totally 37,899 participants had a complete data of cardiac magnetic resonance (CMR), of which 940 patients with diabetes were included, and all the participants completed follow-up. LV-GRS, LV-GCS, and LV-GLS were measured by completely automated CMR with tissue tagging. Cox proportional hazards regression analysis and C-index was performed to evaluate the association between the strain parameters and the new-onset HF in patients suffering from diabetes. Results: The average age of the 940 participants was 57.67 ± 6.97 years, with males comprising 66.4% of the overall population. With an average follow-up period of 166.82 ± 15.26 months, 35 (3.72%) patients reached the endpoint (emergence of new-onset HF). Significant associations were found for the three strain parameters and the new-onset HF (LV-GRS-hazard ratio [HR]: 0.946, 95% CI: 0.916-0.976; LV-GCS-HR: 1.162, 95% CI: 1.086-1.244; LV-GCS-HR: 1.181, 95% CI: 1.082-1.289). LV-GRS, LV-GCS, and LV-GLS were closely related to the related indicators to HF, and showed a high relationship to new-onset HF in individuals with diabetes at 5 and 10 years: LV-GRS: 0.75 (95% CI, 0.41-0.94) and 0.76 (95% CI, 0.44-0.98), respectively; LV-GCS: 0.80 (95% CI, 0.50-0.96) and 0.75 (95% CI, 0.41-0.98), respectively; LV-GLS: 0.72 (95% CI, 0.40-0.93) and 0.76 (95% CI, 0.48-0.97), respectively. In addition, age, sex, body mass index (BMI), and presence of hypertension or coronary artery disease (CAD) made no impacts on the association between the global strain parameters and the incidence of HF. Conclusion: LV-GRS, LV-GCS, and LV-GLS is significantly related to new-onset HF in patients with diabetes at 5 and 10 years.

ANTsX neuroimaging-derived structural phenotypes of UK Biobank.

UK Biobank is a large-scale epidemiological resource for investigating prospective correlations between various lifestyle, environmental, and genetic factors with health and disease progression. In addition to individual subject information obtained through surveys and physical examinations, a comprehensive neuroimaging battery consisting of multiple modalities provides imaging-derived phenotypes (IDPs) that can serve as biomarkers in neuroscience research. In this study, we augment the existing set of UK Biobank neuroimaging structural IDPs, obtained from well-established software libraries such as FSL and FreeSurfer, with related measurements acquired through the Advanced Normalization Tools Ecosystem. This includes previously established cortical and subcortical measurements defined, in part, based on the Desikan-Killiany-Tourville atlas. Also included are morphological measurements from two recent developments: medial temporal lobe parcellation of hippocampal and extra-hippocampal regions in addition to cerebellum parcellation and thickness based on the Schmahmann anatomical labeling. Through predictive modeling, we assess the clinical utility of these IDP measurements, individually and in combination, using commonly studied phenotypic correlates including age, fluid intelligence, numeric memory, and several other sociodemographic variables. The predictive accuracy of these IDP-based models, in terms of root-mean-squared-error or area-under-the-curve for continuous and categorical variables, respectively, provides comparative insights between software libraries as well as potential clinical interpretability. Results demonstrate varied performance between package-based IDP sets and their combination, emphasizing the need for careful consideration in their selection and utilization.

Muscle loss phenotype in COPD is associated with adverse outcomes in the UK Biobank.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory disorder with systemic consequences that can cause a muscle loss phenotype (MLP), which is characterized by the loss of muscle mass, muscle strength, or loss of both muscle and fat mass. There are limited data comparing the individual traits of MLP with clinical outcomes in a large unbiased cohort of COPD patients. Our aim was to determine the proportion of patients who met criteria for MLP in an unbiased sample of COPD patients at the population-level. We also determined if specific MLP features were associated with all-cause and COPD-related mortality. METHODS: A retrospective population-based cohort analysis of the UK Biobank was performed. COPD was defined by a FEV1/FVC ratio < 0.7, physician established diagnosis of COPD, or those with a COPD-related hospitalization before baseline assessment. MLP included one or more of the following: 1) Low fat-free mass index (FFMI) on bioelectric impedance analysis (BIA) or 2) Appendicular skeletal muscle index (ASMI) on BIA, 3) Low muscle strength defined by handgrip strength (HGS), or 4) Low muscle and fat mass based on body mass index (BMI). Cox regression was used to determine the association between MLP and all-cause or COPD-related mortality. All models were adjusted for sex, age at assessment, ethnicity, BMI, alcohol use, smoking status, prior cancer diagnosis and FEV1/FVC ratio. RESULTS: There were 55,782 subjects (56% male) with COPD followed for a median of 70.1 months with a mean(± SD) age at assessment of 59 ± 7.5 years, and FEV1% of 79.2 ± 18.5. Most subjects had mild (50.4%) or moderate (42.8%) COPD. Many patients had evidence of a MLP, which was present in 53.4% of COPD patients (34% by ASMI, 26% by HGS). Of the 5,608 deaths in patients diagnosed with COPD, 907 were COPD-related. After multivariate adjustment, COPD subjects with MLP had a 30% higher hazard-ratio for all-cause death and 70% higher hazard-ratio for COPD-related death. CONCLUSIONS: Evidence of MLP is common in a large population-based cohort of COPD and is associated with higher risk for all-cause and COPD-related mortality.

Association of Cantonese dietary patterns with mortality risk in older Chinese: a 16-year follow-up of a Guangzhou Biobank cohort study.

Background: Evidence about the associations between Cantonese dietary patterns and mortality is scarce. We examined the prospective association of the dietary pattern with all-cause, cancer and cardiovascular disease (CVD) mortality in older Chinese. Methods: We included 19 598 participants of a Guangzhou Biobank cohort study aged 50+ years, who were recruited from 2003 to 2006 and followed up until July, 2022. The diet was assessed by using a 300-item validated food frequency questionnaire. The food items were collapsed into 27 food groups. Factor analysis (FA) was used to identify dietary patterns. Multivariable Cox regression produced hazard ratios (HRs) and 95% confidence intervals (CIs) for mortality. Results: During 305 410 person-years, 4966 deaths including 1971 CVD, 1565 cancer and 1436 other-causes occurred. Four dietary patterns were identified by FA. No association of the vegetable-based dietary pattern with all-cause, CVD and cancer mortality was found. Compared with the lowest quartile of the healthy Cantonese dietary pattern score, the highest quartile showed lower risks of all-cause (HR 0.86, 95% CI 0.80-0.94) and CVD mortality (HR 0.84, 95% CI 0.72-0.97). The highest quartile of the nut and fruit dietary pattern showed lower risks of all-cause (HR 0.92, 95% CI 0.85-0.99) and CVD mortality (HR 0.82, 95% CI 0.72-0.93), while the unhealthy western dietary pattern was associated with a higher risk of all-cause (HR 1.10, 95% CI 1.01-1.19) and cerebrovascular disease mortality (HR 1.28, 95% CI 1.03-1.58). Conclusion: We have first identified four dietary patterns based on the Cantonese cuisine and found that healthy Cantonese and nut and fruit dietary patterns were associated with lower risks of all-cause and CVD mortality, whereas the unhealthy western dietary pattern was associated with a higher risk of all-cause and cerebrovascular disease mortality.

Joint association of serum urate and healthy diet with chronic obstructive pulmonary disease incidence: results from the UK Biobank study.

Background: The role of serum urate (SU) levels in the development of chronic obstructive pulmonary disease (COPD) remains a topic of debate, and it is unclear whether a healthy diet can mitigate the impact of SU on COPD risk. The objective of this study is to examine whether and to what extent a healthy diet can reduce the risk of COPD in relation to SU levels. Methods: The cohort analysis included 155 403 participants from the UK Biobank. SU levels were measured at the time of recruitment. A healthy diet score was calculated based on the consumption of vegetables, fruits, fish, processed meats, unprocessed red meat, whole grains, and refined grains. The Cox proportional hazards model was used to analyze the associations between SU levels, a healthy diet score, and the risk of COPD. Results: During a follow-up period of 1 409 969 person-years, 2918 incident cases of COPD were identified. Compared with the lowest SU level group, the hazard ratio (HR) and 95% confidence interval (CI) for COPD were 1.17 (1.03, 1.34) for participants with the highest SU level (hyperuricemia), indicating a positive association. Additionally, a dose-response relationship was observed between SU levels and the incidence of COPD (P-value for overall <0.0001). In the combined effect analysis, compared to individuals with high SU (hyperuricemia) + a low diet score (diet score <4), those with normal SU + a high diet score (diet score ≥4) had a HR (95% CI) of 0.75 (0.65, 0.87) for COPD. Conclusions: In summary, there is a positive association between SU levels and the risk of COPD. Furthermore, a healthier diet can mitigate the risk of COPD associated with high SU levels.

Pharmacogenomic profiling of intra-tumor heterogeneity using a large organoid biobank of liver cancer.

Inter- and intra-tumor heterogeneity is a major hurdle in primary liver cancer (PLC) precision therapy. Here, we establish a PLC biobank, consisting of 399 tumor organoids derived from 144 patients, which recapitulates histopathology and genomic landscape of parental tumors, and is reliable for drug sensitivity screening, as evidenced by both in vivo models and patient response. Integrative analysis dissects PLC heterogeneity, regarding genomic/transcriptomic characteristics and sensitivity to seven clinically relevant drugs, as well as clinical associations. Pharmacogenomic analysis identifies and validates multi-gene expression signatures predicting drug response for better patient stratification. Furthermore, we reveal c-Jun as a major mediator of lenvatinib resistance through JNK and ß-catenin signaling. A compound (PKUF-01) comprising moieties of lenvatinib and veratramine (c-Jun inhibitor) is synthesized and screened, exhibiting a marked synergistic effect. Together, our study characterizes the landscape of PLC heterogeneity, develops predictive biomarker panels, and identifies a lenvatinib-resistant mechanism for combination therapy.

Perinatal photoperiod associations with bipolar disorder and depression: A systematic literature review and cross-sectional analysis of the UK Biobank database.

Season-of-birth associations with psychiatric disorders point to environmental (co-)aetiological factors such as natural photoperiod that, if clarified, may allow interventions toward prevention. We systematically reviewed the literature concerning season-of-birth and bipolar disorder and depression and explored associations between the perinatal natural photoperiod and these outcomes in a cross-sectional analysis of the UK Biobank database. We used mean daily photoperiod and relative photoperiod range (relative to the mean) in the 3rd trimester and, separately, in the first 3 months post birth as metrics. From review, increased risk of depression with late spring birth is compatible with increased odds of probable single episode-, probable recurrent-, and diagnosed depression (OR 2.85 95 %CI 1.6-5.08, OR 2.20 95 %CI 1.57-3.1, and OR 1.48 95 %CI 1.11-1.97, respectively) with increasing 3rd trimester relative photoperiod range for participants who experienced relatively non-extreme daily photoperiods. Risk of bipolar disorder with winter-spring birth contrasted with no consistent patterns of perinatal photoperiod metric associations with bipolar disorder in the UK Biobank. As natural photoperiod varies by both time-of-year and latitude, perinatal natural photoperiods (and a hypothesized mechanism of action via the circadian timing system and/or serotonergic circuitry associated with the dorsal raphe nucleus) may reconcile inconsistencies in season-of-birth associations. Further studies are warranted.