Harnessing Artificial Intelligence in Multimodal Omics Data Integration: Paving the Path for the Next Frontier in Precision Medicine.

The integration of multiomics data with detailed phenotypic insights from electronic health records marks a paradigm shift in biomedical research, offering unparalleled holistic views into health and disease pathways. This review delineates the current landscape of multimodal omics data integration, emphasizing its transformative potential in generating a comprehensive understanding of complex biological systems. We explore robust methodologies for data integration, ranging from concatenation-based to transformation-based and network-based strategies, designed to harness the intricate nuances of diverse data types. Our discussion extends from incorporating large-scale population biobanks to dissecting high-dimensional omics layers at the single-cell level. The review underscores the emerging role of large language models in artificial intelligence, anticipating their influence as a near-future pivot in data integration approaches. Highlighting both achievements and hurdles, we advocate for a concerted effort toward sophisticated integration models, fortifying the foundation for groundbreaking discoveries in precision medicine.

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.

Large-scale cross-ancestry genome-wide meta-analysis of serum urate.

Hyperuricemia is an essential causal risk factor for gout and is associated with cardiometabolic diseases. Given the limited contribution of East Asian ancestry to genome-wide association studies of serum urate, the genetic architecture of serum urate requires exploration. A large-scale cross-ancestry genome-wide association meta-analysis of 1,029,323 individuals and ancestry-specific meta-analysis identifies a total of 351 loci, including 17 previously unreported loci. The genetic architecture of serum urate control is similar between European and East Asian populations. A transcriptome-wide association study, enrichment analysis, and colocalization analysis in relevant tissues identify candidate serum urate-associated genes, including CTBP1, SKIV2L, and WWP2. A phenome-wide association study using polygenic risk scores identifies serum urate-correlated diseases including heart failure and hypertension. Mendelian randomization and mediation analyses show that serum urate-associated genes might have a causal relationship with serum urate-correlated diseases via mediation effects. This study elucidates our understanding of the genetic architecture of serum urate control.

Association between genetic risk and adherence to healthy lifestyle for developing age-related hearing loss.

BACKGROUND: Previous studies have shown that lifestyle/environmental factors could accelerate the development of age-related hearing loss (ARHL). However, there has not yet been a study investigating the joint association among genetics, lifestyle/environmental factors, and adherence to healthy lifestyle for risk of ARHL. We aimed to assess the association between ARHL genetic variants, lifestyle/environmental factors, and adherence to healthy lifestyle as pertains to risk of ARHL. METHODS: This case-control study included 376,464 European individuals aged 40 to 69 years, enrolled between 2006 and 2010 in the UK Biobank (UKBB). As a replication set, we also included a total of 26,523 individuals considered of European ancestry and 9834 individuals considered of African-American ancestry through the Penn Medicine Biobank (PMBB). The polygenic risk score (PRS) for ARHL was derived from a sensorineural hearing loss genome-wide association study from the FinnGen Consortium and categorized as low, intermediate, high, and very high. We selected lifestyle/environmental factors that have been previously studied in association with hearing loss. A composite healthy lifestyle score was determined using seven selected lifestyle behaviors and one environmental factor. RESULTS: Of the 376,464 participants, 87,066 (23.1%) cases belonged to the ARHL group, and 289,398 (76.9%) individuals comprised the control group in the UKBB. A very high PRS for ARHL had a 49% higher risk of ARHL than those with low PRS (adjusted OR, 1.49; 95% CI, 1.36-1.62; P < .001), which was replicated in the PMBB cohort. A very poor lifestyle was also associated with risk of ARHL (adjusted OR, 3.03; 95% CI, 2.75-3.35; P < .001). These risk factors showed joint effects with the risk of ARHL. Conversely, adherence to healthy lifestyle in relation to hearing mostly attenuated the risk of ARHL even in individuals with very high PRS (adjusted OR, 0.21; 95% CI, 0.09-0.52; P < .001). CONCLUSIONS: Our findings of this study demonstrated a significant joint association between genetic and lifestyle factors regarding ARHL. In addition, our analysis suggested that lifestyle adherence in individuals with high genetic risk could reduce the risk of ARHL.

Polygenic risk score-based phenome-wide association study of head and neck cancer across two large biobanks.

BACKGROUND: Numerous observational studies have highlighted associations of genetic predisposition of head and neck squamous cell carcinoma (HNSCC) with diverse risk factors, but these findings are constrained by design limitations of observational studies. In this study, we utilized a phenome-wide association study (PheWAS) approach, incorporating a polygenic risk score (PRS) derived from a wide array of genomic variants, to systematically investigate phenotypes associated with genetic predisposition to HNSCC. Furthermore, we validated our findings across heterogeneous cohorts, enhancing the robustness and generalizability of our results. METHODS: We derived PRSs for HNSCC and its subgroups, oropharyngeal cancer and oral cancer, using large-scale genome-wide association study summary statistics from the Genetic Associations and Mechanisms in Oncology Network. We conducted a comprehensive investigation, leveraging genotyping data and electronic health records from 308,492 individuals in the UK Biobank and 38,401 individuals in the Penn Medicine Biobank (PMBB), and subsequently performed PheWAS to elucidate the associations between PRS and a wide spectrum of phenotypes. RESULTS: We revealed the HNSCC PRS showed significant association with phenotypes related to tobacco use disorder (OR, 1.06; 95% CI, 1.05-1.08; P = 3.50 × 10-15), alcoholism (OR, 1.06; 95% CI, 1.04-1.09; P = 6.14 × 10-9), alcohol-related disorders (OR, 1.08; 95% CI, 1.05-1.11; P = 1.09 × 10-8), emphysema (OR, 1.11; 95% CI, 1.06-1.16; P = 5.48 × 10-6), chronic airway obstruction (OR, 1.05; 95% CI, 1.03-1.07; P = 2.64 × 10-5), and cancer of bronchus (OR, 1.08; 95% CI, 1.04-1.13; P = 4.68 × 10-5). These findings were replicated in the PMBB cohort, and sensitivity analyses, including the exclusion of HNSCC cases and the major histocompatibility complex locus, confirmed the robustness of these associations. Additionally, we identified significant associations between HNSCC PRS and lifestyle factors related to smoking and alcohol consumption. CONCLUSIONS: The study demonstrated the potential of PRS-based PheWAS in revealing associations between genetic risk factors for HNSCC and various phenotypic traits. The findings emphasized the importance of considering genetic susceptibility in understanding HNSCC and highlighted shared genetic bases between HNSCC and other health conditions and lifestyles.

Genome-wide association analyses using machine learning-based phenotyping reveal genetic architecture of occupational creativity and overlap with psychiatric disorders.

Creativity is known to be heritable and exhibits familial aggregation with psychiatric disorders; however, the complex nature of their relationship has not been well-established. In the present study, we demonstrate that using an expanded and validated machine learning (ML)-based phenotyping of occupational creativity (OC) can allow us to further understand the trait of creativity, which was previously difficult to define and study. We conducted the largest genome-wide association study (GWAS) on OC with 241,736 participants from the UK Biobank and identified 25 lead variants that have not yet been reported and three candidate causal genes that were previously associated with educational attainment and psychiatric disorders. We found extensive genetic overlap between OC and psychiatric disorders with mixed effect direction through various post-GWAS analyses, including the bivariate causal mixture model. In addition, we discovered a strongly genetic correlation between our original GWAS and the GWAS adjusted for education years (rg = 0.95). Our GWAS analysis via ML-based phenotyping contributes to the understanding of the genetic architecture of creativity, which may inform genetic discovery and genetic prediction in human cognition and psychiatric disorders.

Shared genetic architectures of educational attainment in East Asian and European populations.

Educational attainment (EduYears), a heritable trait often used as a proxy for cognitive ability, is associated with various health and social outcomes. Previous genome-wide association studies (GWASs) on EduYears have been focused on samples of European (EUR) genetic ancestries. Here we present the first large-scale GWAS of EduYears in people of East Asian (EAS) ancestry (n = 176,400) and conduct a cross-ancestry meta-analysis with EduYears GWAS in people of EUR ancestry (n = 766,345). EduYears showed a high genetic correlation and power-adjusted transferability ratio between EAS and EUR. We also found similar functional enrichment, gene expression enrichment and cross-trait genetic correlations between two populations. Cross-ancestry fine-mapping identified refined credible sets with a higher posterior inclusion probability than single population fine-mapping. Polygenic prediction analysis in four independent EAS and EUR cohorts demonstrated transferability between populations. Our study supports the need for further research on diverse ancestries to increase our understanding of the genetic basis of educational attainment.

An interpretable Alzheimer's disease oligogenic risk score informed by neuroimaging biomarkers improves risk prediction and stratification.

Introduction: Stratification of Alzheimer's disease (AD) patients into risk subgroups using Polygenic Risk Scores (PRS) presents novel opportunities for the development of clinical trials and disease-modifying therapies. However, the heterogeneous nature of AD continues to pose significant challenges for the clinical broadscale use of PRS. PRS remains unfit in demonstrating sufficient accuracy in risk prediction, particularly for individuals with mild cognitive impairment (MCI), and in allowing feasible interpretation of specific genes or SNPs contributing to disease risk. We propose adORS, a novel oligogenic risk score for AD, to better predict risk of disease by using an optimized list of relevant genetic risk factors. Methods: Using whole genome sequencing data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort (n = 1,545), we selected 20 genes that exhibited the strongest correlations with FDG-PET and AV45-PET, recognized neuroimaging biomarkers that detect functional brain changes in AD. This subset of genes was incorporated into adORS to assess, in comparison to PRS, the prediction accuracy of CN vs. AD classification and MCI conversion prediction, risk stratification of the ADNI cohort, and interpretability of the genetic information included in the scores. Results: adORS improved AUC scores over PRS in both CN vs. AD classification and MCI conversion prediction. The oligogenic model also refined risk-based stratification, even without the assistance of APOE, thus reflecting the true prevalence rate of the ADNI cohort compared to PRS. Interpretation analysis shows that genes included in adORS, such as ATF6, EFCAB11, ING5, SIK3, and CD46, have been observed in similar neurodegenerative disorders and/or are supported by AD-related literature. Discussion: Compared to conventional PRS, adORS may prove to be a more appropriate choice of differentiating patients into high or low genetic risk of AD in clinical studies or settings. Additionally, the ability to interpret specific genetic information allows the focus to be shifted from general relative risk based on a given population to the information that adORS can provide for a single individual, thus permitting the possibility of personalized treatments for AD.

Impacts of gender and lifestyle on the association between depressive symptoms and cardiovascular disease risk in the UK Biobank.

We investigated the effects of gender and lifestyle on the association between frequency of depressive symptoms and CVD risk. The UK Biobank is a national prospective cohort study that recruited 502,505 participants aged 40-69 years between 2006 and 2010. Participants without CVD were classified as having low, moderate, high, or very high frequency of depressive symptoms according to the number of days they felt depressed in a 2-week period. UKBB data include self-reported questionnaires covering lifestyle behaviors such as smoking, physical activity, eating habits, and sleep duration. The primary outcomes included incident CVD including coronary artery disease, ischemic stroke, hemorrhagic stroke, peripheral artery disease, atrial fibrillation/flutter, and heart failure. Cox proportional hazard models were used to evaluate the effects of gender and lifestyle on the association of frequency of depressive symptoms and CVD risk. During a median follow-up of 8.9 years, 27,394 (6.3%) developed CVD. The frequency of depressive symptoms increased the risk of CVD according to low, moderate, high, and very high frequency of depressive symptoms (P for trend < 0.001). The adjusted CVD risk was 1.38-fold higher for participants with very high frequency of depressive symptoms compared to those with low frequency of depressive symptoms (HR 1.38, 95% CI 1.24-1.53, P < 0.001). The correlation between frequency of depressive symptoms and CVD risk was more remarkable in females than in males. In participants with high or very high frequency of depressive symptoms, the individual lifestyle factors of no current smoking, non-obesity, non-abdominal obesity, regular physical activity, and appropriate sleep respectively was associated with lower CVD risk by 46% (HR 0.54, 95% CI 0.48-0.60, P < 0.001), 36% (HR 0.64, 95% CI 0.58-0.70, P < 0.001), 31% (HR 0.69, 95% CI 0.62-0.76, P < 0.001), 25% (HR 0.75, 95% CI 0.68-0.83, P < 0.001), and 22% (HR 0.78, 95% CI 0.71-0.86, P < 0.001). In this large prospective cohort study, a higher frequency of depressive symptoms at baseline was significantly associated with increased risk of CVD in the middle-aged population, and this relationship was prominent in women. In the middle-aged population with depressive symptoms, engaging in a healthier lifestyle could prevent CVD risk.

Leveraging genetic overlap between irritability and psychiatric disorders to identify genetic variants of major psychiatric disorders.

Irritability is a heritable core mental trait associated with several psychiatric illnesses. However, the genomic basis of irritability is unclear. Therefore, this study aimed to 1) identify the genetic variants associated with irritability and investigate the associated biological pathways, genes, and tissues as well as single-nucleotide polymorphism (SNP)-based heritability; 2) explore the relationships between irritability and various traits, including psychiatric disorders; and 3) identify additional and shared genetic variants for irritability and psychiatric disorders. We conducted a genome-wide association study (GWAS) using 379,506 European samples (105,975 cases and 273,531 controls) from the UK Biobank. We utilized various post-GWAS analyses, including linkage disequilibrium score regression, the bivariate causal mixture model (MiXeR), and conditional and conjunctional false discovery rate approaches. This GWAS identified 15 independent loci associated with irritability; the total SNP heritability estimate was 4.19%. Genetic correlations with psychiatric disorders were most pronounced for major depressive disorder (MDD) and bipolar II disorder (BD II). MiXeR analysis revealed polygenic overlap with schizophrenia (SCZ), bipolar I disorder (BD I), and MDD. Conditional false discovery rate analyses identified additional loci associated with SCZ (number [n] of additional SNPs = 105), BD I (n = 54), MDD (n = 107), and irritability (n = 157). Conjunctional false discovery rate analyses identified 85, 41, and 198 shared loci between irritability and SCZ, BD I, and MDD, respectively. Multiple genetic loci were associated with irritability and three main psychiatric disorders. Given that irritability is a cross-disorder trait, these findings may help to elucidate the genomics of psychiatric disorders.

Identifying genetic variants for amyloid ß in subcortical vascular cognitive impairment.

Background: The genetic basis of amyloid ß (Aß) deposition in subcortical vascular cognitive impairment (SVCI) is still unknown. Here, we investigated genetic variants involved in Aß deposition in patients with SVCI. Methods: We recruited a total of 110 patients with SVCI and 424 patients with Alzheimer's disease-related cognitive impairment (ADCI), who underwent Aß positron emission tomography and genetic testing. Using candidate AD-associated single nucleotide polymorphisms (SNPs) that were previously identified, we investigated Aß-associated SNPs that were shared or distinct between patients with SVCI and those with ADCI. Replication analyses were performed using the Alzheimer's Disease Neuroimaging Initiative (ADNI) and Religious Orders Study and Rush Memory and Aging Project cohorts (ROS/MAP). Results: We identified a novel SNP, rs4732728, which showed distinct associations with Aß positivity in patients with SVCI (P interaction = 1.49 × 10-5); rs4732728 was associated with increased Aß positivity in SVCI but decreased Aß positivity in ADCI. This pattern was also observed in ADNI and ROS/MAP cohorts. Prediction performance for Aß positivity in patients with SVCI increased (area under the receiver operating characteristic curve = 0.780; 95% confidence interval = 0.757-0.803) when rs4732728 was included. Cis-expression quantitative trait loci analysis demonstrated that rs4732728 was associated with EPHX2 expression in the brain (normalized effect size = -0.182, P = 0.005). Conclusion: The novel genetic variants associated with EPHX2 showed a distinct effect on Aß deposition between SVCI and ADCI. This finding may provide a potential pre-screening marker for Aß positivity and a candidate therapeutic target for SVCI.

Large multi-ethnic genetic analyses of amyloid imaging identify new genes for Alzheimer disease.

Amyloid PET imaging has been crucial for detecting the accumulation of amyloid beta (Aß) deposits in the brain and to study Alzheimer's disease (AD). We performed a genome-wide association study on the largest collection of amyloid imaging data (N = 13,409) to date, across multiple ethnicities from multicenter cohorts to identify variants associated with brain amyloidosis and AD risk. We found a strong APOE signal on chr19q.13.32 (top SNP: APOE ɛ4; rs429358; ß = 0.35, SE = 0.01, P = 6.2 × 10-311, MAF = 0.19), driven by APOE ɛ4, and five additional novel associations (APOE ε2/rs7412; rs73052335/rs5117, rs1081105, rs438811, and rs4420638) independent of APOE ɛ4. APOE ɛ4 and ε2 showed race specific effect with stronger association in Non-Hispanic Whites, with the lowest association in Asians. Besides the APOE, we also identified three other genome-wide loci: ABCA7 (rs12151021/chr19p.13.3; ß = 0.07, SE = 0.01, P = 9.2 × 10-09, MAF = 0.32), CR1 (rs6656401/chr1q.32.2; ß = 0.1, SE = 0.02, P = 2.4 × 10-10, MAF = 0.18) and FERMT2 locus (rs117834516/chr14q.22.1; ß = 0.16, SE = 0.03, P = 1.1 × 10-09, MAF = 0.06) that all colocalized with AD risk. Sex-stratified analyses identified two novel female-specific signals on chr5p.14.1 (rs529007143, ß = 0.79, SE = 0.14, P = 1.4 × 10-08, MAF = 0.006, sex-interaction P = 9.8 × 10-07) and chr11p.15.2 (rs192346166, ß = 0.94, SE = 0.17, P = 3.7 × 10-08, MAF = 0.004, sex-interaction P = 1.3 × 10-03). We also demonstrated that the overall genetic architecture of brain amyloidosis overlaps with that of AD, Frontotemporal Dementia, stroke, and brain structure-related complex human traits. Overall, our results have important implications when estimating the individual risk to a population level, as race and sex will needed to be taken into account. This may affect participant selection for future clinical trials and therapies.

ICD2Vec: Mathematical representation of diseases.

BACKGROUND: The International Classification of Diseases (ICD) codes represent the global standard for reporting disease conditions. The current ICD codes connote direct human-defined relationships among diseases in a hierarchical tree structure. Representing the ICD codes as mathematical vectors helps to capture nonlinear relationships in medical ontologies across diseases. METHODS: We propose a universally applicable framework called "ICD2Vec" designed to provide mathematical representations of diseases by encoding corresponding information. First, we present the arithmetical and semantic relationships between diseases by mapping composite vectors for symptoms or diseases to the most similar ICD codes. Second, we investigated the validity of ICD2Vec by comparing the biological relationships and cosine similarities among the vectorized ICD codes. Third, we propose a new risk score called IRIS, derived from ICD2Vec, and demonstrate its clinical utility with large cohorts from the UK and South Korea. RESULTS: Semantic compositionality was qualitatively confirmed between descriptions of symptoms and ICD2Vec. For example, the diseases most similar to COVID-19 were found to be the common cold (ICD-10: J00), unspecified viral hemorrhagic fever (ICD-10: A99), and smallpox (ICD-10: B03). We show the significant associations between the cosine similarities derived from ICD2Vec and the biological relationships using disease-to-disease pairs. Furthermore, we observed significant adjusted hazard ratios (HR) and area under the receiver operating characteristics (AUROC) between IRIS and risks for eight diseases. For instance, the higher IRIS for coronary artery disease (CAD) can be the higher probability for the incidence of CAD (HR: 2.15 [95% CI 2.02-2.28] and AUROC: 0.587 [95% CI 0.583-0.591]). We identified individuals at substantially increased risk of CAD using IRIS and 10-year atherosclerotic cardiovascular disease risk (adjusted HR: 4.26 [95% CI 3.59-5.05]). CONCLUSIONS: ICD2Vec, a proposed universal framework for converting qualitatively measured ICD codes into quantitative vectors containing semantic relationships between diseases, exhibited a significant correlation with actual biological significance. In addition, the IRIS was a significant predictor of major diseases in a prospective study using two large-scale datasets. Based on this clinical validity and utility evidence, we suggest that publicly available ICD2Vec can be used in diverse research and clinical practices and has important clinical implications.

Genome-wide polygenic risk scores for hypertensive disease during pregnancy can also predict the risk for long-term cardiovascular disease.

BACKGROUND: Hypertensive disorders during pregnancy are associated with the risk of long-term cardiovascular disease after pregnancy, but it has not yet been determined whether genetic predisposition for hypertensive disorders during pregnancy can predict the risk for long-term cardiovascular disease. OBJECTIVE: This study aimed to evaluate the risk for long-term atherosclerotic cardiovascular disease according to polygenic risk scores for hypertensive disorders during pregnancy. STUDY DESIGN: Among UK Biobank participants, we included European-descent women (n=164,575) with at least 1 live birth. Participants were divided according to genetic risk categorized by polygenic risk scores for hypertensive disorders during pregnancy (low risk, score ≤25th percentile; medium risk, score 25th∼75th percentile; high risk, score >75th percentile), and were evaluated for incident atherosclerotic cardiovascular disease, defined as the new occurrence of one of the following: coronary artery disease, myocardial infarction, ischemic stroke, or peripheral artery disease. RESULTS: Among the study population, 2427 (1.5%) had a history of hypertensive disorders during pregnancy, and 8942 (5.6%) developed incident atherosclerotic cardiovascular disease after enrollment. Women with high genetic risk for hypertensive disorders during pregnancy had a higher prevalence of hypertension at enrollment. After enrollment, women with high genetic risk for hypertensive disorders during pregnancy had an increased risk for incident atherosclerotic cardiovascular disease, including coronary artery disease, myocardial infarction, and peripheral artery disease, compared with those with low genetic risk, even after adjustment for history of hypertensive disorders during pregnancy. CONCLUSION: High genetic risk for hypertensive disorders during pregnancy was associated with increased risk for atherosclerotic cardiovascular disease. This study provides evidence on the informative value of polygenic risk scores for hypertensive disorders during pregnancy in prediction of long-term cardiovascular outcomes later in life.

Association of glaucoma and lifestyle with incident cardiovascular disease: a longitudinal prospective study from UK Biobank.

The shared pathophysiological features of the cerebrovascular disease (CVD) and glaucoma suggest an association between the two diseases. Using the prospective UK Biobank cohort, we examined the associations between glaucoma and incident CVD and assessed the extent to which a healthy lifestyle reduced the CVD risk in subjects with glaucoma, using a scoring system consisting of four factors: current smoking, obesity, regular physical activity, and a healthy diet. During a mean follow-up time of 8.9 years, 22,649 (4.9%) incident CVD cases were documented. Multivariable Cox regression analyses revealed that subjects with glaucoma were significantly more likely to exhibit incident CVD (hazard ratio [HR]:1.19, 95% confidence interval [CI] 1.03-1.37; p = 0.016) than controls. In the further subgroup analyses, glaucoma increased incident CVD risk both in the young (40-55 years) and the old (56-70 years) and in both sexes, with higher risk in the young (HR: 1.33, CI 1.02-1.74) and female subjects (HR: 1.32, CI 1.14-1.52). When we analyze the associations between glaucoma and incident CVD by lifestyle factors, the highest absolute risks were observed in individuals with both glaucoma and an unhealthy lifestyle (HR: 2.66, CI 2.22-3.19). In conclusion, glaucoma was an independent risk factor for incident CVD. A healthy lifestyle was associated with a substantially lower risk for CVD incidence among adults with glaucoma.

Discovering comorbid diseases using an inter-disease interactivity network based on biobank-scale PheWAS data.

MOTIVATION: Understanding comorbidity is essential for disease prevention, treatment and prognosis. In particular, insight into which pairs of diseases are likely or unlikely to co-occur may help elucidate the potential relationships between complex diseases. Here, we introduce the use of an inter-disease interactivity network to discover/prioritize comorbidities. Specifically, we determine disease associations by accounting for the direction of effects of genetic components shared between diseases, and categorize those associations as synergistic or antagonistic. We further develop a comorbidity scoring algorithm to predict whether diseases are more or less likely to co-occur in the presence of a given index disease. This algorithm can handle networks that incorporate relationships with opposite signs. RESULTS: We finally investigate inter-disease associations among 427 phenotypes in UK Biobank PheWAS data and predict the priority of comorbid diseases. The predicted comorbidities were verified using the UK Biobank inpatient electronic health records. Our findings demonstrate that considering the interaction of phenotype associations might be helpful in better predicting comorbidity. AVAILABILITY AND IMPLEMENTATION: The source code and data of this study are available at https://github.com/dokyoonkimlab/DiseaseInteractiveNetwork. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Transferability of Alzheimer Disease Polygenic Risk Score Across Populations and Its Association With Alzheimer Disease-Related Phenotypes.

Importance: Polygenic risk scores (PRSs), which aggregate the genetic effects of single-nucleotide variants identified in genome-wide association studies (GWASs), can help distinguish individuals at a high genetic risk for Alzheimer disease (AD). However, genetic studies have predominantly focused on populations of European ancestry. Objective: To evaluate the transferability of a PRS for AD in the Korean population using summary statistics from a prior GWAS of European populations. Design, Setting, and Participants: This cohort study developed a PRS based on the summary statistics of a large-scale GWAS of a European population (the International Genomics of Alzheimer Project; 21 982 AD cases and 41 944 controls). This PRS was tested for an association with AD dementia and its related phenotypes in 1634 Korean individuals, who were recruited from 2013 to 2019. The association of a PRS based on a GWAS of a Japanese population (the National Center for Geriatrics and Gerontology; 3962 AD cases and 4074 controls) and a transancestry meta-analysis of European and Japanese GWASs was also evaluated. Data were analyzed from December 2020 to June 2021. Main Outcomes and Measures: Risk of AD dementia, amnestic mild cognitive impairment (aMCI), earlier symptom onset, and amyloid ß deposition (Aß). Results: A total of 1634 Korean patients (969 women [59.3%]), including 716 individuals (43.6%) with AD dementia, 222 (13.6%) with aMCI, and 699 (42.8%) cognitively unimpaired controls, were analyzed in this study. The mean (SD) age of the participants was 71.6 (9.0) years. Higher PRS was associated with a higher risk of AD dementia independent of APOE ɛ4 status in the Korean population (OR, 1.95; 95% CI, 1.40-2.72; P < .001). Furthermore, PRS was associated with aMCI, earlier symptom onset, and Aß deposition independent of APOE ɛ4 status. The PRS based on a transancestry meta-analysis of data sets comprising 2 distinct ancestries showed a slightly improved accuracy. Conclusions and Relevance: In this cohort study, a PRS derived from a European GWAS identified individuals at a high risk for AD dementia in the Korean population. These findings emphasize the transancestry transferability and clinical value of PRSs and suggest the importance of enriching diversity in genetic studies of AD.

The anti-obesity effect of mulberry leaf (Mori Folium) extracts was increased by bioconversion with Pectinex.

Mulberry leaf (Mori Folium) extract (MLE) is known to have anti-obesity effects. In this study, the enhanced effects of MLE after bioconversion treatment using Pectinex (BMLE) on obesity were explored, and the underlying mechanisms were investigated using the active components, neochlorogenic acid (5-CQA) and cryptochlorogenic acid (4-CQA), whose amounts were increased by bioconversion of MLE. Both MLE and BMLE inhibited lipid accumulation in 3T3-L1 adipocytes without cytotoxicity and suppressed the expression of CCAAT/enhancer-binding protein alpha (C/EBPα). In addition, MLE and BMLE decreased high-fat diet-induced adipose tissue mass expansion. Notably, BMLE significantly increased antiadipogenic and anti-obesity effects compared to MLE in vitro and in vivo. The active ingredients increased by bioconversion, 5-CQA and 4-CQA, inhibited the protein levels of C/EBPα and the mRNA levels of stearoyl-CoA desaturase 1 (Scd1). These findings provide new insights into the therapeutic possibility of using bioconversion of MLE, by which upregulation of 5-CQA and 4-CQA potently inhibits adipogenesis.

Associations between polygenic risk of coronary artery disease and type 2 diabetes, lifestyle, and cardiovascular mortality: A prospective UK Biobank study.

Background: Previous studies primarily targeted the ability of polygenic risk scores (PRSs) to predict a specific disease, and only a few studies have investigated the association between genetic risk scores and cardiovascular (CV) mortality. We assessed PRSs for coronary artery disease (CAD) and type 2 diabetes (T2DM) as the predictive factors for CV mortality, independent of traditional risk factors, and further investigated the additive effect between lifestyle behavior and PRS on CV mortality. Methods: We used genetic and phenotypic data from UK Biobank participants aged 40-69 years at baseline, collected with standardized procedures. Genome-wide PRSs were constructed using >6 million genetic variants. Cox proportional hazard models were used to analyze the relationship between PRS and CV mortality with stratification by age, sex, disease status, and lifestyle behavior. Results: Of 377,909 UK Biobank participants having European ancestry, 3,210 (0.8%) died due to CV disease during a median follow-up of 8.9 years. CV mortality risk was significantly associated with CAD PRS [low vs. very high genetic risk groups, CAD PRS hazard ratio (HR) 2.61 (2.02-3.36)] and T2DM PRS [HR 2.08 (1.58-2.73)], respectively. These relationships remained significant even after an adjustment for a comprehensive range of demographic and clinical factors. In the very high genetic risk group, adherence to an unfavorable lifestyle was further associated with a substantially increased risk of CV mortality [favorable vs. unfavorable lifestyle with very high genetic risk for CAD PRS, HR 8.31 (5.12-13.49); T2DM PRS, HR 5.84 (3.39-10.04)]. Across all genetic risk groups, 32.1% of CV mortality was attributable to lifestyle behavior [population attributable fraction (PAF) 32.1% (95% CI 28.8-35.3%)] and 14.1% was attributable to smoking [PAF 14.1% (95% CI 12.4-15.7%)]. There was no evidence of significant interaction between PRSs and age, sex, or lifestyle behavior in predicting the risk of CV mortality. Conclusion: PRSs for CAD or T2DM and lifestyle behaviors are the independent predictive factors for future CV mortality in the white, middle-aged population. PRS-based risk assessment could be useful to identify the individuals who need intensive behavioral or therapeutic interventions to reduce the risk of CV mortality.

Polygenic risk for type 2 diabetes, lifestyle, metabolic health, and cardiovascular disease: a prospective UK Biobank study.

BACKGROUND: Few studies have examined associations between genetic risk for type 2 diabetes (T2D), lifestyle, clinical risk factors, and cardiovascular disease (CVD). We aimed to investigate the association of and potential interactions among genetic risk for T2D, lifestyle behavior, and metabolic risk factors with CVD. METHODS: A total of 345,217 unrelated participants of white British descent were included in analyses. Genetic risk for T2D was estimated as a genome-wide polygenic risk score constructed from > 6 million genetic variants. A favorable lifestyle was defined in terms of four modifiable lifestyle components, and metabolic health status was determined according to the presence of metabolic syndrome components. RESULTS: During a median follow-up of 8.9 years, 21,865 CVD cases (6.3%) were identified. Compared with the low genetic risk group, participants at high genetic risk for T2D had higher rates of overall CVD events, CVD subtypes (coronary artery disease, peripheral artery disease, heart failure, and atrial fibrillation/flutter), and CVD mortality. Individuals at very high genetic risk for T2D had a 35% higher risk of CVD than those with low genetic risk (HR 1.35 [95% CI 1.19 to 1.53]). A significant gradient of increased CVD risk was observed across genetic risk, lifestyle, and metabolic health status (P for trend > 0.001). Those with favorable lifestyle and metabolically healthy status had significantly reduced risk of CVD events regardless of T2D genetic risk. This risk reduction was more apparent in young participants (≤ 50 years). CONCLUSIONS: Genetic risk for T2D was associated with increased risks of overall CVD, various CVD subtypes, and fatal CVD. Engaging in a healthy lifestyle and maintaining metabolic health may reduce subsequent risk of CVD regardless of genetic risk for T2D.