Genome-wide study on 72,298 individuals in Korean biobank data for 76 traits

New insights on underlying shared genetic architectures and causality of underweight and depression in East Asian populations

BACKGROUND

Extensive evidence links a lower body mass index (BMI) to higher odds of depression in individuals of East Asian ancestry, differing from patterns observed in European populations. However, the shared genetic etiology underlying underweight and depression remains unclear in East Asian populations.

METHOD

Utilizing large-scale genome-wide association study (GWAS) data, we investigated the shared genetics between BMI (N = 323,298) and depression traits (N = 286,052) through linkage disequilibrium score regression, cross-trait meta-analysis and colocalization analysis. Additionally, we evaluated causal associations using bidirectional Mendelian randomization (MR) analysis.

RESULTS

We found a significantly negative genetic correlation between BMI and depression (rg = -0.19, P = 0.002). The cross-trait analysis identified 26 shared risk SNPs, including FTO and more. Moreover, the risk gene AGBL4 showed evidence of colocalization. Using the MR method, lower BMI was associated with higher odds of depression in individuals of East Asian ancestry (OR: 1.14, 95 % CI: 1.02 to 1.28, P = 0.021) but no reverse causal effect was observed.

CONCLUSIONS

Our study indicates a genetic correlation, shared risk genes, and causality between underweight and depression in East Asian populations. These findings provide insights into the potential mechanisms behind their comorbidity and inform the future development of therapeutics for East Asian populations.

Prader-Willi syndrome gene expression profiling of obese and non-obese patients reveals transcriptional changes in CLEC4D and ANXA3

OBJECTIVES

We aimed to characterize genetic alterations in Prader-Willi syndrome (PWS) using whole genome microarrays.

METHODS

We performed mRNA expression microarray analysis using RNA isolated from whole blood of 25 PWS patients and 25 age-matched controls. After preprocessing the data to reduce heterogeneity, differentially expressed genes (DEGs) between groups were identified using a linear regression model package. Reactome pathway analysis was performed for upregulated and downregulated genes using EnrichR. Correlations between gene expression levels and clinical factors were estimated using Spearman's rank correlation coefficient.

RESULTS

Of 21,488 probes examined in the microarray analysis, 4,156 were detected. Fifty-two genes had different expression levels in children with PWS compared with healthy controls (36 genes upregulated and 16 downregulated). Twelve genes were upregulated and 13 were downregulated in obese PWS patients compared with normal-weight PWS (NW-PWS) patients. The C-type lectin domain family 4 member D (CLEC4D) was upregulated in both PWS (vs. control) and obese-PWS (vs. NW-PWS) patients, and CLEC4D expression was also correlated with body mass index-standard deviation score in PWS patients. Among the genes upregulated in obese PWS vs. NW-PWS, Annexin A3 (ANXA3), potassium inwardly rectifying channel subfamily J member 15 (KCNJ15), and selenium binding protein 1 (SELENBP1) were upregulated in obese-control vs. NW-control. Gene ontology analysis revealed that upregulated DEGs were significantly enriched in biological processes, including pathways involved in myeloid dendritic cell activation associated with CLEC4D.

CONCLUSIONS

This study revealed differences in gene expression between obese and NW-PWS patients. The regulation of macrophage infiltration by CLEC4D suggests a possible mechanism associated with obesity-related complications in PWS.

Dissecting cross-population polygenic heterogeneity across respiratory and cardiometabolic diseases

Biological mechanisms underlying multimorbidity remain elusive. To dissect the polygenic heterogeneity of multimorbidity in twelve complex traits across populations, we leveraged biobank resources of genome-wide association studies (GWAS) for 232,987 East Asian individuals (the 1st and 2nd cohorts of BioBank Japan) and 751,051 European individuals (UK Biobank and FinnGen). Cross-trait analyses of respiratory and cardiometabolic diseases, rheumatoid arthritis, and smoking identified negative genetic correlations between respiratory and cardiometabolic diseases in East Asian individuals, opposite from the positive associations in European individuals. Associating genome-wide polygenic risk scores (PRS) with 325 blood metabolome and 2917 proteome biomarkers supported the negative cross-trait genetic correlations in East Asian individuals. Bayesian pathway PRS analysis revealed a negative association between asthma and dyslipidemia in a gene set of peroxisome proliferator-activated receptors. The pathway suggested heterogeneity of cell type specificity in the enrichment analysis of the lung single-cell RNA-sequencing dataset. Our study highlights the heterogeneous pleiotropy of immunometabolic dysfunction in multimorbidity.

System genetic analysis of intestinal cancer and periodontitis development as influenced by aging and diabesity using Collaborative Cross mice

It is increasingly recognized that young, chow-fed inbred mice poorly model the complexity of human carcinogenesis. In humans, age and adiposity are major risk factors for malignancies, but most genetically engineered mouse models (GEMM) induce carcinogenesis too rapidly to study these influences. Standard strains, such as C57BL/6, commonly used in GEMMs, further limit the exploration of aging and metabolic health effects. A similar challenge arises in modeling periodontitis, a disease influenced by aging, diabesity, and genetic architecture. We propose using diverse mouse populations with hybrid vigor, such as the Collaborative Cross (CC) × ApcMin hybrid, to slow disease progression and better model human colorectal cancer (CRC) and comorbidities. This perspective highlights the advantages of this model, where delayed carcinogenesis reveals interactions with aging and adiposity. Unlike ApcMin mice, which develop cancer rapidly, CC × ApcMin hybrids recapitulate human-like progression. This facilitates the identification of modifier loci affecting inflammation, diet susceptibility, organ size, and polyposis distribution. The CC × ApcMin model offers a transformative platform for studying CRC as a disease of adulthood, reflecting its complex interplay with aging and comorbidities. The insights gained from this approach will enhance early detection, management, and treatment strategies for CRC and related conditions.

Natural selection shaped the protective effect of the mtDNA lineage against obesity in Han Chinese populations

Mitochondria play a key role in lipid metabolism, and mitochondrial DNA (mtDNA) mutations are thus considered to affect obesity susceptibility by altering oxidative phosphorylation and mitochondrial function. In this study, we investigate mtDNA variants that may affect obesity risk in 2877 Han Chinese individuals from 3 independent populations. The association analysis of 16 basal mtDNA haplogroups with body mass index, waist circumference, and waist-to-hip ratio reveals that only haplogroup M7 is significantly negatively correlated with all three adiposity-related anthropometric traits in the overall cohort, verified by the analysis of a single population, i.e., the Zhengzhou population. Furthermore, subhaplogroup analysis suggests that M7b1a1 is the most likely haplogroup associated with a decreased obesity risk, and the variation T12811C (causing Y159H in ND5) harbored in M7b1a1 may be the most likely candidate for altering the mitochondrial function. Specifically, we find that proportionally more nonsynonymous mutations accumulate in M7b1a1 carriers, indicating that M7b1a1 is either under positive selection or subject to a relaxation of selective constraints. We also find that nuclear variants, especially in DACT2 and PIEZO1, may functionally interact with M7b1a1.

Addressing overfitting bias due to sample overlap in polygenic risk scoring

INTRODUCTION

Numerous studies on Alzheimer's disease polygenic risk scores (PRSs) overlook sample overlap between International Genomics of Alzheimer's Project (IGAP) and target datasets like Alzheimer's Disease Neuroimaging Initiative (ADNI).

METHODS

To address this, we developed overlap-adjusted PRS (OA PRS) and tested it on simulated data to assess biases from different scenarios by varying training, testing, and overlap proportions. OA PRS was used to adjust for sample bias in simulations; then, we applied OA PRS to IGAP and ADNI datasets and validated through visual diagnosis.

RESULTS

OA PRS effectively adjusted for sample overlap in all simulation scenarios, as well as for IGAP and ADNI. The original IGAP PRS showed an inflated area under the receiver operating characteristic (AUROC: 0.915) on overlapping samples. OA PRS reduced the AUROC to 0.726, closely aligning with the AUROC of non-overlapping samples (0.712). Further, visual diagnostics confirmed the effectiveness of our adjustments.

DISCUSSION

With OA PRS, we were able to adjust the IGAP summary-based PRS for the overlapped ADNI samples, allowing the dataset to be fully used without the risk of overfitting.

HIGHLIGHTS

Sample overlap between large Alzheimer's disease (AD) cohorts poses overfitting bias when using AD polygenic risk scores (PRSs). This study highlighted the effectiveness of overlap-adjusted PRS (OA -PRS) in mitigating overfitting and improving the accuracy of PRS estimations. New PRSs based on adjusted effect sizes showed increased power in association with clinical features.

Elevated thyroid-stimulating hormone levels, independent of Hashimoto's thyroiditis, increase thyroid cancer risk: Insights from genetic and clinical evidence

PURPOSE

Hashimoto's thyroiditis (HT) is a prevalent autoimmune disorder and thyroid cancer (TC) is the most prevalent endocrine malignancy. Recent debates have focused on whether HT increases the risk of developing TC. This study combined Mendelian randomization (MR) and observational methods to investigate the potential causal relationship between HT and TC risk.

METHODS

First, we performed two-sample MR and multivariable MR (MVMR) analysis using the genome-wide association studies (GWAS) data from multiple databases, including European and East Asian populations, to estimate the effect of HT and thyroid-stimulating hormone (TSH) levels on TC risk. Second, we conducted an observational study using data from the National Health and Nutrition Examination Survey (NHANES) database and evaluated the association between HT, TSH, and TC prevalence through logistic regression model and restricted cubic spline model.

RESULTS

Our MR findings revealed no significant association between HT and TC risk in both populations. However, elevated TSH levels significantly increased TC and papillary thyroid carcinoma (PTC) risk, while lower TSH levels were associated with reduced TC risk. Further MVMR analysis and an observational study confirmed this. Additionally, our observational study also indicated no significant relationship between HT and TC prevalence and abnormal TSH levels correlated with higher TC risk.

CONCLUSION

HT was not a TC risk factor, but high TSH levels increased TC risk. Controlling TSH within normal ranges through thyroid hormone replacement was recommended to reduce TC risk in HT patients with elevated TSH levels, even those without symptoms.

Missense variants in FRS3 affect body mass index in populations of diverse ancestries

Obesity is associated with adverse effects on health and quality of life. Improved understanding of its underlying pathophysiology is essential for developing counteractive measures. To search for sequence variants with large effects on BMI, we perform a multi-ancestry meta-analysis of 13 genome-wide association studies on BMI, including data derived from 1,534,555 individuals of European ancestry, 339,657 of Asian ancestry, and 130,968 of African ancestry. We identify an intergenic 262,760 base pair deletion at the MC4R locus that associates with 4.11 kg/m2 higher BMI per allele, likely through downregulation of MC4R. Moreover, a rare FRS3 missense variant, p.Glu115Lys, only found in individuals from Finland, associates with 1.09 kg/m2 lower BMI per allele. We also detect three other low-frequency FRS3 missense variants that associate with BMI with smaller effects and are enriched in different ancestries. We characterize FRS3 as a BMI-associated gene, encoding an adaptor protein known to act downstream of BDNF and TrkB, which regulate appetite, food intake, and energy expenditure through unknown signaling pathways. The work presented here contributes to the biological foundation of obesity by providing a convincing downstream component of the BDNF-TrkB pathway, which could potentially be targeted for obesity treatment.

Lessons from national biobank projects utilizing whole-genome sequencing for population-scale genomics

Large-scale national biobank projects utilizing whole-genome sequencing have emerged as transformative resources for understanding human genetic variation and its relationship to health and disease. These initiatives, which include the UK Biobank, All of Us Research Program, Singapore's PRECISE, Biobank Japan, and the National Project of Bio-Big Data of Korea, are generating unprecedented volumes of high-resolution genomic data integrated with comprehensive phenotypic, environmental, and clinical information. This review examines the methodologies, contributions, and challenges of major WGS-based national genome projects worldwide. We first discuss the landscape of national biobank initiatives, highlighting their distinct approaches to data collection, participant recruitment, and phenotype characterization. We then introduce recent technological advances that enable efficient processing and analysis of large-scale WGS data, including improvements in variant calling algorithms, innovative methods for creating multi-sample VCFs, optimized data storage formats, and cloud-based computing solutions. The review synthesizes key discoveries from these projects, particularly in identifying expression quantitative trait loci and rare variants associated with complex diseases. Our review introduces the latest findings from the National Project of Bio-Big Data of Korea, which has advanced our understanding of population-specific genetic variation and rare diseases in Korean and East Asian populations. Finally, we discuss future directions and challenges in maximizing the impact of these resources on precision medicine and global health equity. This comprehensive examination demonstrates how large-scale national genome projects are revolutionizing genetic research and healthcare delivery while highlighting the importance of continued investment in diverse, population-specific genomic resources.

Assessment of polygenic risk score performance in East Asian populations for ten common diseases

Polygenic risk score (PRS) uses genetic variants to assess disease susceptibility. While PRS performance is well-studied in Europeans, its accuracy in East Asians is less explored. This study evaluated PRSs for ten diseases in the Health Examinees (HEXA) cohort (n = 55,870) in Korea. Single-population PRSs were constructed using PRS-CS, LDpred2, and Lassosum based on East Asian GWAS summary statistics (sample sizes: 51,442-341,204), while cross-population PRSs were developed using PRS-CSx and CT-SLEB by integrating European and East Asian GWAS data. PRS-CS consistently outperformed other single-population methods across key metrics, including the likelihood ratio test (LRT), odds ratio per standard deviation (perSD OR), net reclassification improvement (NRI), and area under the curve (AUC). Cross-population PRSs further improved predictive performance, with average increases of 1.08-fold (LRT), 1.07-fold (perSD OR), and 1.15-fold (NRI) across seven diseases with statistical significance, and a 1.01-fold improvement in AUC. Differences in R² between single- and cross-population PRSs were statistically significant for five diseases, showing an average increase of 1.13%. Cross-population PRSs achieved 87.8% of the predictive performance observed in European PRSs. These findings highlight the benefits of integrating European GWAS data while underscoring the need for larger East Asian datasets to improve prediction accuracy.

Large-scale cross-trait genetic analysis highlights shared genetic backgrounds of autoimmune diseases

Disorders associated with the immune system burden multiple organs, although the shared biology exists across the diseases. Preceding family-based studies reveal that immune diseases are heritable to varying degrees, providing the basis for immunogenomics. The recent cost reduction in genetic analysis intensively promotes biobank-scale studies and the development of frameworks for statistical genetics. The accumulating multi-layer omics data, including genome-wide association studies (GWAS) and RNA-sequencing at single-cell resolution, enable us to dissect the genetic backgrounds of immune-related disorders. Although autoimmune and allergic diseases are generally categorized into different disease categories, epidemiological studies reveal the high incidence of autoimmune and allergic disease complications, suggesting the shared genetics and biology between the disease categories. Biobank resources and consortia cover multiple immune-related disorders to accumulate phenome-wide associations of genetic variants and enhance researchers to analyze the shared and heterogeneous genetic backgrounds. The emerging post-GWAS and integrative multi-omics analyses provide genetic and biological insights into the multicategorical disease associations.

Comparing Alzheimer's genes in African, European, and Amerindian induced pluripotent stem cell-derived microglia

INTRODUCTION

Genome-wide association studies (GWAS) studies in Alzheimer's disease (AD) demonstrate ancestry-specific loci. Previous studies in the regulatory architecture have only been conducted in Europeans (EUs), thus studies in additional ancestries are needed. Given the prevalence of AD genes expressed in microglia, we initiated our studies in induced pluripotent stem cell (iPSC) -derived microglia.

METHODS

We created iPSC-derived microglia from 13 individuals of either high Amerindian (AI), African (AF), or EU global ancestry, including both AD and controls. RNA-seq, ATAC-seq, and pathway analyses were compared between ancestries in both AD and non-AD genes.

RESULTS

Twelve AD genes were differentially expressed genes (DEGs) and/or accessible between ancestries, including ABI3, CTSB, and MS4A6A. A total of 5% of all genes had differential ancestral expression, but differences in accessibility were less than 1%. The DEGs were enriched in known AD pathways.

DISCUSSION

This resource will be valuable in evaluating AD in admixed populations and other neurological disorders and understanding the AD risk differences between populations.

HIGHLIGHTS

First comparison of the genomics of AI, AF, and EU microglia. Report differences in expression and accessibility of AD genes between ancestries. Ancestral expression differences are greater than differences in accessibility. Good transcriptome correlation was seen between brain and iPSC-derived microglia. Differentially expressed AD genes were in known AD pathways.

Genome-wide association studies in a large Korean cohort identify novel quantitative trait loci for 36 traits and illuminate their genetic architectures

Genome-wide association studies (GWAS) have been predominantly conducted in populations of European ancestry, limiting opportunities for biological discovery in diverse populations. We report GWAS findings from 153,950 individuals across 36 quantitative traits in the Korean Cancer Prevention Study-II (KCPS2) Biobank. We discovered 301 novel genetic loci in KCPS2, including an association between thyroid-stimulating hormone and CD36. Meta-analysis with the Korean Genome and Epidemiology Study, Biobank Japan, Taiwan Biobank, and UK Biobank identified 4,588 loci that were not significant in any contributing GWAS. We describe differences in genetic architectures across these East Asian and European samples. We also highlight East Asian specific associations, including a known pleiotropic missense variant in ALDH2, which fine-mapping identified as a likely causal variant for a diverse set of traits. Our findings provide insights into the genetic architecture of complex traits in East Asian populations and highlight how broadening the population diversity of GWAS samples can aid discovery.

Investigation of the causal relationship between breast cancer and thyroid cancer: a set of two-sample bidirectional Mendelian randomization study

PURPOSE

A potential association between breast (BC) and thyroid cancer (TC) has been observed. We investigated if the relationship between BC and TC is causal using bidirectional Mendelian randomization (MR) in Asian and European populations.

METHODS

BC-linked single nucleotide polymorphisms (SNPs) were acquired from a genome-wide association study (GWAS) conducted by the Breast Cancer Association Consortium and Biobank Japan. The most recent TC GWAS data were obtained from the FinnGen Project and National Biobank of Korea. We assessed the potential causal relationship between BC and TC using various MR methods, including inverse-variance-weighting (IVW). Sensitivity, heterogeneity, and pleiotropic tests were performed to assess reliability.

RESULTS

We found a bidirectional causal association between BC and TC within Europeans (IVW, TC on BC: odds ratio [OR] 1.090, 95% confidence interval [CI]: 1.012-1.173, P = 0.023; BC on TC: OR 1.265, 95% CI: 1.158-1.381, P < 0.001). A one-way causal relationship between BC susceptibility and TC risk was found in Asians (IVW BC on TC: OR 2.274, 95% CI: 2.089-2.475, P < 0.001). Subsequently, we identified a noteworthy bidirectional causal relationship between estrogen receptor (ER)-positive BC and TC (IVW, TC on ER-positive BC: OR 1.104, 95% CI: 1.001-1.212, P = 0.038; ER-positive BC on TC: OR 1.223, 95%CI: 1.072-1.395, P = 0.003), but not ER-negative BC and TC in Europeans.

CONCLUSION

We revealed a reciprocal causal association between ER-positive BC and TC. These findings establish a theoretical framework for the simultaneous surveillance and treatment of BC and TC.

Genome-Wide Association Analysis of Rapid Decline in Lung Function: Analysis From the Korean Genome and Epidemiology Study

BACKGROUND

A rapid decline in forced expiratory volume in 1 second (FEV1) is considered an important phenotype of the development of chronic obstructive pulmonary disease (COPD). However, the associations between specific genetic variants (single-nucleotide polymorphisms; SNPs) and this phenotype remain uncertain.

METHODS

We enrolled 6,516 individuals from the Korean Genome and Epidemiology Study (KoGES). A rapid decline in FEV1 was defined as an annual decrease of FEV1 ≥ 60 mL/year. A multivariable logistic regression model was used to assess the associations between SNP variants and the rapid decline in FEV1. Considering the significant impact of smoking on lung function, a subgroup analysis based on smoking history was also conducted.

RESULTS

A genome-wide association analysis of the rapid decline in FEV1 identified 15 association signals (P < 5.0 × 10-8). Among the 15 nucleotide variants, rs9833533 and rs1496255 have been previously reported to be associated with lung function development. In the subgroup analysis, rs16951883 (adjusted odds ratio [aOR], 3.24; P = 5.87 × 10-8) was the most significant SNP associated with rapid decline in FEV1 among never smokers, followed by rs41476549, rs16840064, and rs1350110. Conversely, among ever smokers, rs10959478 (aOR, 4.74; P = 8.27 × 10-7) showed the highest significance, followed by rs6805861, rs9833533, and rs16906215.

CONCLUSION

We identified 15 nucleotide variants linked to a rapid decline in FEV1, including two SNPs previously reported to be associated with lung function development. Additional SNPs, which were associated with COPD, may be found using novel phenotypes.

Potentially causal association between immunoglobulin G N-glycans and cardiometabolic diseases: Bidirectional two-sample Mendelian randomization study

BACKGROUND

Observational studies support that altered immunoglobulin G (IgG) N-glycosylation and inflammatory factors are associated with cardiometabolic diseases (CMDs); nevertheless, the causality between them remains unclear.

METHODS

Two-sample Mendelian randomization (MR) analyses were conducted to systematically investigate the bidirectional causality between IgG N-glycans and nine CMDs in both East Asians and Europeans.

RESULTS

In the forward MR analysis, the univariable MR analysis presented suggestive causality of 14 and eight genetically instrumented IgG N-glycans with CMDs in East Asians and Europeans, respectively; the multivariable MR analysis showed that ten and 11 pairs of glycan-CMD associations were identified in East Asian and European populations, respectively. In the reverse MR analysis, based on East Asians and Europeans, the univariable MR analysis presented suggestive causality of seven and 12 genetically instrumented CMDs with IgG N-glycans, respectively; the multivariable MR analysis presented that six and five CMD-glycan causality were found in East Asian and Europeans, respectively.

CONCLUSIONS

The comprehensive MR analyses provide suggestive evidence of bidirectional causality between IgG N-glycans and CMDs. This work helps to understand the molecular mechanism of the occurrence/progression of CMDs, optimize existing and develop new strategies to prevent CMDs, and contribute to the early identification of high-risk groups of CMDs.

Proteo-genomic analyses in relatively lean Chinese adults identify proteins and pathways that affect general and central adiposity levels

Adiposity is an established risk factor for multiple diseases, but the causal relationships of different adiposity types with circulating protein biomarkers have not been systematically investigated. We examine the causal associations of general and central adiposity with 2923 plasma proteins among 3977 Chinese adults (mean BMI = 23.9 kg/m²). Genetically-predicted body mass index (BMI), body fat percentage (BF%), waist circumference (WC), and waist-to-hip ratio (WHR) are significantly (FDR < 0.05) associated with 399, 239, 436, and 283 proteins, respectively, with 80 proteins associated with all four and 275 with only one adiposity trait. WHR is associated with the most proteins (n = 90) after adjusting for other adiposity traits. These associations are largely replicated in Europeans (mean BMI = 27.4 kg/m²). Two-sample Mendelian randomisation (MR) analyses in East Asians using cis-protein quantitative trait locus (cis-pQTLs) identified in GWAS find 30/2 proteins significantly affect levels of BMI/WC, respectively, with 10 showing evidence of colocalisation, and seven (inter-alpha-trypsin inhibitor heavy chain H3, complement factor B, EGF-containing fibulin-like extracellular matrix protein 1, thioredoxin domain-containing protein 15, alpha-2-antiplasmin, fibronectin, mimecan) are replicated in separate MR using different cis-pQTLs identified in Europeans. These findings identified potential novel mechanisms and targets, to our knowledge, for improved treatment and prevention of obesity and associated diseases.

Estimation of a genetic Gaussian network using GWAS summary data

A genetic Gaussian network of multiple phenotypes, constructed through the inverse matrix of the genetic correlation matrix, is informative for understanding the biological dependencies of the phenotypes. However, its estimation may be challenging because the genetic correlation estimates are biased due to estimation errors and idiosyncratic pleiotropy inherent in GWAS summary statistics. Here, we introduce a novel approach called estimation of genetic graph (EGG), which eliminates the estimation error bias and idiosyncratic pleiotropy bias with the same techniques used in multivariable Mendelian randomization. The genetic network estimated by EGG can be interpreted as shared common biological contributions between phenotypes, conditional on others. We use both simulations and real data to demonstrate the superior efficacy of our novel method in comparison with the traditional network estimators.

Discrepancy Between Genetically Predicted and Observed BMI Predicts Incident Type 2 Diabetes

OBJECTIVE

Obesity is a key predictor of type 2 diabetes (T2D). However, metabolic complications are not solely due to increased BMI. We hypothesized that differences between genetically predicted BMI and observed BMI (BMI-diff) could reflect deviation from individual set point and may predict incident T2D.

RESEARCH DESIGN AND METHODS

From the UK Biobank cohort, we selected participants of European ancestry without T2D (n = 332,154). The polygenic risk score for BMI was calculated via Bayesian regression and continuous shrinkage priors (PRS-CS). According to the BMI-diff, the 10-year risk of T2D was assessed using multivariable Cox proportional hazards model. Independent data from the Korean Genome and Epidemiology Study (KoGES) cohort from South Korea (n = 7,430) were used for replication.

RESULTS

Participants from the UK Biobank were divided into train (n = 268,041) and test set (n = 115,119) to establish genetically predicted BMI. In the test set, the genetically predicted BMI explained 7.1% of the variance of BMI, and there were 3,599 T2D cases (3.1%) during a 10-year follow-up. Participants in the higher quintiles of BMI-diff (more obese than genetically predicted) had significantly higher risk of T2D than those in the lowest quintile after adjusting for observed BMI: the adjusted hazard ratio of the 1st quintile (vs. 5th quintile) was 1.61 (95% CI 1.26-2.05, P < 0.001). Results were consistent among individuals in the KoGES study. Moreover, higher BMI than predicted was associated with impaired insulin sensitivity.

CONCLUSIONS

Having a higher BMI than genetically predicted is associated with an increased risk of T2D. These findings underscore the potential to reassess T2D risk based on individual levels of obesity using genetic thresholds for BMI.

Pharmacogenetic study of CES1 gene and enalapril efficacy

Enalapril is an orally administered angiotensin-converting enzyme inhibitor which is widely prescribed to treat hypertension, chronic kidney disease, and heart failure. It is an ester prodrug that needs to be activated by carboxylesterase 1 (CES1). CES1 is a hepatic hydrolase that in vivo biotransforms enalapril to its active form enalaprilat in order to produce its desired pharmacological impact. Several single nucleotide polymorphisms in CES1 gene are reported to alter the catalytic activity of CES1 enzyme and influence enalapril metabolism. G143E, L40T, G142E, G147C, Y170D, and R171C can completely block the enalapril metabolism. Some polymorphisms like Q169P, E220G, and D269fs do not completely block the CES1 function; however, they reduce the catalytic activity of CES1 enzyme. The prevalence of these polymorphisms is not the same among all populations which necessitate to consider the genetic panel of respective population before prescribing enalapril. These genetic variations are also responsible for interindividual variability of CES1 enzyme activity which ultimately affects the pharmacokinetics and pharmacodynamics of enalapril. The current review summarizes the CES1 polymorphisms which influence the enalapril metabolism and efficacy. The structure of CES1 catalytic domain and important amino acids impacting the catalytic activity of CES1 enzyme are also discussed. This review also highlights the importance of pharmacogenomics in personalized medicine.

Big data in sarcoidosis

PURPOSE OF REVIEW

This review provides an overview of recent advancements in sarcoidosis research, focusing on collaborative networks, phenotype characterization, and molecular studies. It highlights the importance of collaborative efforts, phenotype characterization, and the integration of multilevel molecular data for advancing sarcoidosis research and paving the way toward personalized medicine.

RECENT FINDINGS

Sarcoidosis exhibits heterogeneous clinical manifestations influenced by various factors. Efforts to define sarcoidosis endophenotypes show promise, while technological advancements enable extensive molecular data generation. Collaborative networks and biobanks facilitate large-scale studies, enhancing biomarker discovery and therapeutic protocols.

SUMMARY

Sarcoidosis presents a complex challenge due to its unknown cause and heterogeneous clinical manifestations. Collaborative networks, comprehensive phenotype delineation, and the utilization of cutting-edge technologies are essential for advancing our understanding of sarcoidosis biology and developing personalized medicine approaches. Leveraging large-scale epidemiological resources and biobanks and integrating multilevel molecular data offer promising avenues for unraveling the disease's heterogeneity and improving patient outcomes.

Genetic predisposition to bone mineral density and their health conditions in East Asians

Osteoporosis, a condition defined by low BMD (typically < -2.5 SD), causes a higher fracture risk and leads to significant economic, social, and clinical impacts. Genome-wide studies mainly in Caucasians have found many genetic links to osteoporosis, fractures, and BMD, with limited research in East Asians (EAS). We investigated the genetic aspects of BMD in 86 716 individuals from the Taiwan Biobank and their causal links to health conditions within EAS. A genome-wide association study (GWAS) was conducted, followed by observational studies, polygenic risk score assessments, and genetic correlation analyses to identify associated health conditions linked to BMD. GWAS and gene-based GWAS studies identified 78 significant SNPs and 75 genes related to BMD, highlighting pathways like Hedgehog, WNT-mediated, and TGF-β. Our cross-trait linkage disequilibrium score regression analyses for BMD and osteoporosis consistently validated their genetic correlations with BMI and type 2 diabetes (T2D) in EAS. Higher BMD was linked to lower osteoporosis risk but increased BMI and T2D, whereas osteoporosis linked to lower BMI, waist circumference, hemoglobinA1c, and reduced T2D risk. Bidirectional Mendelian randomization analyses revealed that a higher BMI causally increases BMD in EAS. However, no direct causal relationships were found between BMD and T2D, or between osteoporosis and either BMI or T2D. This study identified key genetic factors for bone health in Taiwan, and revealed significant health conditions in EAS, particularly highlighting the genetic interplay between bone health and metabolic traits like T2D and BMI.

Genetic determinants of obesity in Korean populations: exploring genome-wide associations and polygenic risk scores

East Asian populations exhibit a genetic predisposition to obesity, yet comprehensive research on these traits is limited. We conducted a genome-wide association study (GWAS) with 93,673 Korean subjects to uncover novel genetic loci linked to obesity, examining metrics such as body mass index, waist circumference, body fat ratio, and abdominal fat ratio. Participants were categorized into non-obese, metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO) groups. Using advanced computational methods, we developed a multifaceted polygenic risk scores (PRS) model to predict obesity. Our GWAS identified significant genetic effects with distinct sizes and directions within the MHO and MUO groups compared with the non-obese group. Gene-based and gene-set analyses, along with cluster analysis, revealed heterogeneous patterns of significant genes on chromosomes 3 (MUO group) and 11 (MHO group). In analyses targeting genetic predisposition differences based on metabolic health, odds ratios of high PRS compared with medium PRS showed significant differences between non-obese and MUO, and non-obese and MHO. Similar patterns were seen for low PRS compared with medium PRS. These findings were supported by the estimated genetic correlation (0.89 from bivariate GREML). Regional analyses highlighted significant local genetic correlations on chromosome 11, while single variant approaches suggested widespread pleiotropic effects, especially on chromosome 11. In conclusion, our study identifies specific genetic loci and risks associated with obesity in the Korean population, emphasizing the heterogeneous genetic factors contributing to MHO and MUO.

Causal relevance of different blood pressure traits on risk of cardiovascular diseases: GWAS and Mendelian randomisation in 100,000 Chinese adults

Elevated blood pressure (BP) is major risk factor for cardiovascular diseases (CVD). Genome-wide association studies (GWAS) conducted predominantly in populations of European ancestry have identified >2,000 BP-associated loci, but other ancestries have been less well-studied. We conducted GWAS of systolic, diastolic, pulse, and mean arterial BP in 100,453 Chinese adults. We identified 128 non-overlapping loci associated with one or more BP traits, including 74 newly-reported associations. Despite strong genetic correlations between populations, we identified appreciably higher heritability and larger variant effect sizes in Chinese compared with European or Japanese ancestry populations. Using instruments derived from these GWAS, multivariable Mendelian randomisation demonstrated that BP traits contribute differently to the causal associations of BP with CVD. In particular, only pulse pressure was independently causally associated with carotid plaque. These findings reinforce the need for studies in diverse populations to understand the genetic determinants of BP traits and their roles in disease risk.

Genome-wide association study and fine-mapping on Korean biobank to discover renal trait-associated variants

BACKGROUND

Chronic kidney disease is a significant health burden worldwide, with increasing incidence. Although several genome- wide association studies (GWAS) have investigated single nucleotide polymorphisms (SNP) associated with kidney trait, most studies were focused on European ancestry.

METHODS

We utilized clinical and genetic information collected from the Korean Genome and Epidemiology Study (KoGES).

RESULTS

More than five million SNPs from 58,406 participants were analyzed. After meta-GWAS, 1,360 loci associated with estimated glomerular filtration rate (eGFR) at a genome-wide significant level (p = 5 × 10-8) were identified. Among them, 399 loci were validated with at least one other biomarker (blood urea nitrogen [BUN] or eGFRcysC) and 149 loci were validated using both markers. Among them, 18 SNPs (nine known ones and nine novel ones) with 20 putative genes were found. The aggregated effect of genes estimated by MAGMA gene analysis showed that these significant genes were enriched in kidney-associated pathways, with the kidney and liver being the most enriched tissues.

CONCLUSION

In this study, we conducted GWAS for more than 50,000 Korean individuals and identified several variants associated with kidney traits, including eGFR, BUN, and eGFRcysC. We also investigated functions of relevant genes using computational methods to define putative causal variants.

The clinical relevance of a polygenic risk score for type 2 diabetes mellitus in the Korean population

The clinical utility of a type 2 diabetes mellitus (T2DM) polygenic risk score (PRS) in the East Asian population remains underexplored. We aimed to examine the potential prognostic value of a T2DM PRS and assess its viability as a clinical instrument. We first established a T2DM PRS for 5490 Korean individuals using East Asian Biobank data (269,487 samples). Subsequently, we assessed the predictive capability of this T2DM PRS in a prospective longitudinal study with baseline data and data from seven additional follow-ups. Our analysis showed that the T2DM PRS could predict the transition of glucose tolerance stages from normal glucose tolerance to prediabetes and from prediabetes to T2DM. Moreover, T2DM patients in the top-decile PRS group were more likely to be treated with insulin (hazard ratio = 1.69, p value = 2.31E-02) than were those in the remaining PRS groups. T2DM PRS values were significantly high in the severe diabetes subgroup, characterized by insulin resistance and β -cell dysfunction (p value = 0.0012). The prediction models with the T2DM PRS had significantly greater Harrel's C-indices than did corresponding models without it. By utilizing prospective longitudinal study data and extensive clinical risk factor information, our analysis provides valuable insights into the multifaceted clinical utility of the T2DM PRS.

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.

Effects of sex and gender on the etiologies and presentation of select internalizing psychopathologies

The internalizing spectrum encompasses a subset of psychopathologies characterized by emotional liability, anhedonia, anxiousness, distress, and fear, and includes, among others, diagnoses of major depressive disorder (MDD), generalized anxiety disorder (GAD), and posttraumatic stress disorder (PTSD). In this review, we describe the vast body of work highlighting a role for sex and gender in the environment, symptom onset, genetic liability, and disorder progression and comorbidities of MDD, GAD, and PTSD. We also point the reader to different language used in diverse fields to describe sexual and gender minorities that may complicate the interpretation of emerging literature from the social sciences, psychiatric and psychological sciences, and genetics. Finally, we identify several gaps in knowledge that we hope serve as launch-points for expanding the scope of psychiatric studies beyond binarized sex-stratification. Despite being under-represented in genomics studies, placing emphasis on inclusion of sexual and gender diverse participants in these works will hopefully improve our understanding of disorder etiology using genetics as one tool to inform how biology (e.g., hormone concentration) and environmental variables (e.g., exposure to traumatic events) contribute to differences in symptom onset, pattern, and long-term trajectory.

Ethnic-specific associations between body mass index and gastric cancer: a Mendelian randomization study in European and Korean populations

BACKGROUND

Given the uncertainties surrounding the associations in previous epidemiological studies, we conducted linear and nonlinear Mendelian randomization (MR) studies to evaluate whether body mass index (BMI) associated with gastric cancer (GC) risk in European and Korean.

METHODS

Genome-wide association study-summary statistics were used from the Pan-UK Biobank, the Genetic Investigation of Anthropometric Traits consortium, the K-CHIP consortium, and BioBank Japan. BMI-associated single nucleotide polymorphisms (SNPs) were used as instrumental variables (IVs) in MR to identify the association between BMI and GC. Both linear and nonlinear MR analyses were performed. Sensitivity analyses were also conducted for individuals below or above a BMI of 24 kg/m2.

RESULTS

The study used 22 and 55 SNPs as IVs for BMI in European and Korean populations, respectively. Genetically predicted BMI was positively associated with GC risk in the European population (Odds ratio per 1 kg/m2 increase; 95% CI = 1.17; 1.01-1.36 using simple median method), but no significant association was observed in the Korean population. However, the nonlinear MR identified a U-shaped association between BMI and GC in the Korean population, with both low and high BMIs associated with increased GC risk. A BMI of 24 kg/m2 presented the lowest risk. Sensitivity analyses did not yield any genome-wide significant SNPs.

CONCLUSION

While MR analysis suggests a linear association between BMI and GC in those of European ancestry, nonlinear MR hints at a U-shaped association in Koreans. This suggests the association between BMI and GC risk may vary according to ethnic ancestry.

Trans-ethnic polygenic risk scores for body mass index: An international hundred K+ cohorts consortium study

BACKGROUND

While polygenic risk scores hold significant promise in estimating an individual's risk of developing a complex trait such as obesity, their application in the clinic has, to date, been limited by a lack of data from non-European populations. As a collaboration model of the International Hundred K+ Cohorts Consortium (IHCC), we endeavored to develop a globally applicable trans-ethnic PRS for body mass index (BMI) through this relatively new international effort.

METHODS

The polygenic risk score (PRS) model was developed, trained and tested at the Center for Applied Genomics (CAG) of The Children's Hospital of Philadelphia (CHOP) based on a BMI meta-analysis from the GIANT consortium. The validated PRS models were subsequently disseminated to the participating sites. Scores were generated by each site locally on their cohorts and summary statistics returned to CAG for final analysis.

RESULTS

We show that in the absence of a well powered trans-ethnic GWAS from which to derive marker SNPs and effect estimates for PRS, trans-ethnic scores can be generated from European ancestry GWAS using Bayesian approaches such as LDpred, by adjusting the summary statistics using trans-ethnic linkage disequilibrium reference panels. The ported trans-ethnic scores outperform population specific-PRS across all non-European ancestry populations investigated including East Asians and three-way admixed Brazilian cohort.

CONCLUSIONS

Here we show that for a truly polygenic trait such as BMI adjusting the summary statistics of a well powered European ancestry study using trans-ethnic LD reference results in a score that is predictive across a range of ancestries including East Asians and three-way admixed Brazilians.

Biobanking as a Tool for Genomic Research: From Allele Frequencies to Cross-Ancestry Association Studies

In recent years, great advances have been made in the field of collection, storage, and analysis of biological samples. Large collections of samples, biobanks, have been established in many countries. Biobanks typically collect large amounts of biological samples and associated clinical information; the largest collections include over a million samples. In this review, we summarize the main directions in which biobanks aid medical genetics and genomic research, from providing reference allele frequency information to allowing large-scale cross-ancestry meta-analyses. The largest biobanks greatly vary in the size of the collection, and the amount of available phenotype and genotype data. Nevertheless, all of them are extensively used in genomics, providing a rich resource for genome-wide association analysis, genetic epidemiology, and statistical research into the structure, function, and evolution of the human genome. Recently, multiple research efforts were based on trans-biobank data integration, which increases sample size and allows for the identification of robust genetic associations. We provide prominent examples of such data integration and discuss important caveats which have to be taken into account in trans-biobank research.