Keiko Hikino

Type 2 diabetes (T2D) is a highly heterogeneous metabolic trait, with a higher prevalence in East Asians. Despite extensive genetic studies focusing mainly on Europeans, how genetic risk for T2D is distributed across biological pathways in East Asians in comparison with Europeans remains incompletely understood. Here, we show results from what is, to our knowledge, the largest genome-wide association study in East Asians, including 596,778 individuals, with a direct comparison to a European study of comparable sample size. We identified 196 loci, including three previously unreported loci. Subsequent multi-ancestry fine-mapping resolved 521 independent causal signals with high precision, revealing that 74% are shared while the remainder are strictly ancestry-specific. Beyond this shared architecture, we observed population differences in regulatory and pathway-level contributions, particularly involving pancreatic regulation and lipid- or adipose-related pathways. Furthermore, constructing a polygenic risk score using the cross-ancestry meta-analysis yielded the most robust predictive performance (AUC = 0.788). These findings clarify how T2D genetic risk is organized across populations, demonstrating that while multi-ancestry integration maximizes clinical predictive power, well-powered single-ancestry studies remain indispensable for uncovering population-specific biological mechanisms.

Bladder cancer is the ninth most common cancer worldwide, caused by genetic and environmental risk factors. Here, we report the findings of a multi-population meta-analysis of genome-wide association studies, including 32,470 individuals with and 1,753,462 without bladder cancer. We identify 70 independent risk loci, of which 43 are novel. Using a 70-marker polygenic risk score (HR = 1.63 per standard deviation), we increase the area under the curve from 0.71 (baseline risk model) to 0.75. Integrative analyses reveal the enrichment of the associated variants within accessible chromatin regions, and of the prioritized genes within pathways for xenobiotic metabolism and smoking behavior. Specifically, we show that the 15q25.1 variant rs71581744-ACCCC/A co-localizes with tissue-specific CHRNA3 expression, modulates mRNA stability, and associates with risk of muscle-invasive bladder cancer among current smokers. Together, these findings substantially expand the known genetic architecture of bladder cancer risk and highlight the germline regulation of smoking behavior as a mechanism driving bladder cancer susceptibility.

Refractive errors (REs) affect over half of the global population, with consequences ranging from blurred vision to blindness. Here we conducted ancestry-stratified and cross-ancestry meta-analyses of genome-wide association studies for RE in people of European (n = 1,495,159), East Asian (n = 121,172) and African (n = 144,737) ancestries. The cross-ancestry meta-analysis identified 932 RE-associated variants, including 241 previously unknown associations, four East Asian-specific associations and one African-specific association. Statistical fine-mapping pinpointed 16 high-confidence putative causal variants, and gene prioritization analyses highlighted 23 genes involved in eye development. We constructed an enhanced polygenic predictor incorporating functional annotations that explained 21.4% of RE variation, effectively stratified the onset, progression and severity of myopia, and achieved an area under the receiver operating characteristic curve of 0.806 for predicting high myopia. Our multi-ancestry genome-wide association study expands substantially the catalog of genetic variants for RE and demonstrates the potential clinical utility of polygenic prediction in identifying high-risk people across diverse populations.

5‐hydroxytryptamine type 3 (5‐HT ₃ ) receptor antagonists are used to treat nausea and vomiting and in the prevention of chemotherapy‐induced, radiation‐induced, and postoperative nausea and vomiting. Most of the 5‐HT ₃ receptor antagonists (i.e., ondansetron, tropisetron, dolasetron, palonosetron, and ramosetron) are metabolized by CYP2D6, but the extent of CYP2D6 involvement varies. CYP2D6 genetic variation can influence the metabolism of these medications, particularly ondansetron and tropisetron, thereby affecting drug efficacy. This guideline is an update to the 2016 Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for CYP2D6 genotype and use of ondansetron and tropisetron and includes updated information on CYP2D6 genetic testing and evidence tables. We summarize evidence from the published literature supporting these associations and provide therapeutic recommendations for 5‐HT ₃ receptor antagonists based on CYP2D6 genotype, particularly where genetic variation is associated with reduced drug efficacy (updates at https://www.clinpgx.org/guideline/PA166251457 ).

Genetic predisposition and alcohol consumption are risk factors for increased blood pressure (BP), but their interactions influencing BP remain understudied. We conducted population-specific and cross-population meta-analyses of genome-wide gene-alcohol (GxAlc) interactions affecting BP in >1.1M individuals from multiple populations. We identified 46 GxAlc interaction loci for BP, including 21 from one-degree-of-freedom interaction tests (PGxAlc<5x10-8; or <0.05/Meff, Meff independent BP associations at P<10-5), and 25 from two-degree-of-freedom tests of main and interaction effects (PGxAlc<0.05/M2df, M2df independent 2df-associations at P2df<5x10-8), including 7 novel and 39 known BP loci. The 12q24 locus highlights the genetic effect of BRAP-rs11066001 on BP, being ~6 times larger in current drinkers than in non-drinkers. Gene prioritization with 46 GxAlc loci identified 15 genes with ≥3 lines of evidence (location, literature, druggability, functional/regulatory annotation, or pathway analyses). Several loci showed sex- and population-specific effects and revealed biological pathways of alcohol’s influence on BP, suggesting mechanisms underlying alcohol-induced hypertension.

Both genetic and environmental factors affect human stature, including overall height and familial short stature (FSS), and it is associated with various health outcomes. However, the study of genetic connections between stature and health conditions remains lacking in East Asian populations. Hence, we conducted parallel genome-wide association studies (GWAS) of body height and FSS in the Han Taiwanese population, aiming to elucidate the genetic influences of stature on health and facilitate the formulation of precision-health strategies. We analyzed large-scale GWAS data on adult height (120,301 Han Taiwanese) and FSS (FSS; 2,050 cases, 27,966 controls) to examine cross-trait genetic correlations across five East Asian biobanks, and applied phenome-wide association studies (PheWAS) and polygenic risk score (PRS) analyses to assess clinical outcomes using Cox proportional hazard models and Kaplan–Meier analyses. We identified 293 loci for height and five for FSS, with cross-biobank genetic correlations linking stature to body size, lung function, and cardiovascular/reproductive traits (atrial flutter/fibrillation [AF], menarche, and endometriosis). PheWAS showed that height PRS increased risks of AF and endometriosis, while FSS PRS had a protective effect against endometriosis. MR analyses showed that taller stature increased AF risk independently and endometriosis risk through menarche/weight, while shorter stature had a weak protective effect against endometriosis. Survival analyses showed the association of higher height PRS with greater AF risk and an earlier divergence of cumulative incidence curves. These time-to-event patterns were consistently replicated using meta-analysis–derived PRSs. The findings highlight stature-related genetic determinants, associated health outcomes, and polygenic risk scores as effective tools for early risk prediction and precision health strategies in East Asian populations.

Mosaic chromosomal alterations (mCAs) accumulate in the brain tissues and are associated with psychiatric disorders. The association between mCAs in circulating blood and schizophrenia (SCZ) and bipolar disorders (BD) has not been fully evaluated. We detected mCAs from blood samples in 2470 SCZ, 3732 BD, and 177,773 control subjects. The associations between mCAs and SCZ or BD were evaluated using age-adjusted logistic regression models, further evaluated in age subgroups. We analyzed the associations between high cell fraction (CF) mosaic events (CF-mCAs >5% or CF-mCAs >10%) and SCZ or BD in the same way. Furthermore, we assessed the interaction between mCAs and genetic risk scores for SCZ or BD. Autosomal mCAs, especially mosaic loss events, increased in both SCZ and BD (SCZ; OR = 1.78, P = 4.9×10^-6, BD; OR = 1.41, P = 0.0025). These associations were highlighted in the young-age subgroup (SCZ; OR = 7.01, P = 1.7×10^-16, BD; OR = 4.01, P = 2.9×10^-8). In addition, the effect sizes of losses increased in a CF-dependent manner in both SCZ and BD. Loss events with high cell fraction interacted with polygenic risk score in SCZ (P = 0.0098). SCZ or BD were characterized by the presence of a high burden of mosaic losses in blood, especially in young age, suggesting the common somatic pathophysiological mechanisms between these psychiatric diseases. The possible interaction between losses and PRS for SCZ supports the genetic and environmental cross-talk in SCZ.

While numerous studies have examined the subjective response to alcohol as an intermediate phenotype to understand its variability, heritability, and predictive capacity for alcohol-related disorders, in-depth analyses linking alcohol reactivity indicators to genetic factors within a large cohort have been absent. Our study aimed to quantify the exact contribution of each genetic variant relevant to the alcohol metabolism to the variability in alcohol response. Specifically, we focused on two primary genes involved in alcohol metabolism (ALDH2 and ADH1B) and three additional loci (ALDH1B1, ALDH1A1, and GCKR) that have been shown to have significant associations with drinking behaviors in Japanese individuals. We conducted the first study to assess the relationship between subjective response to alcohol (SR), evaluated by various assessment subscales, and genetic factors using an intravenous clamp technique in 429 healthy Japanese young adults. By reducing the dimensionality of the data to assess similarity structures, we identified three distinct clusters of SRs and participants. Each participant cluster exhibited a distinct alcohol response profile shaped by specific genetic contributions. Participant cluster 1 demonstrated the strongest response, followed by participant cluster 2, and then participant cluster 3. Participant cluster 1 may also be the most strongly influenced by the allelic status of ALDH2 and ADH1B. SR patterns varied accordingly, and the enrichment of the ALDH2*2 and ADH1B*2, differed across both participant and subscale clusters. Notably, the three participant clusters closely aligned with the three subscale clusters, highlighting a consistent genotype–phenotype relationship. Furthermore, the proportion of variance explained by these genes also varied across subscale clusters. Contrary to known functions, ADH1B showed associations at later timings when ALDH2 associations attenuate. Our three-cluster classification may improve prevention by enabling early identification of individuals at health risk.