Genetic factors explain a major proportion of human height variation, but differences in mean stature have also been found between socio-economic categories suggesting a possible effect of environment. By utilizing a classical twin design which allows decomposing the variation of height into genetic and environmental components, we tested the hypothesis that environmental variation in height is greater in offspring of lower educated parents. Twin data from 29 cohorts including 65,978 complete twin pairs with information on height at ages 1 to 69 years and on parental education were pooled allowing the analyses at different ages and in three geographic-cultural regions (Europe, North America and Australia, and East Asia). Parental education mostly showed a positive association with offspring height, with significant associations in mid-childhood and from adolescence onwards. In variance decomposition modeling, the genetic and environmental variance components of height did not show a consistent relation to parental education. A random-effects meta-regression analysis of the aggregate-level data showed a trend towards greater shared environmental variation of height in low parental education families. In conclusion, in our very large dataset from twin cohorts around the globe, these results provide only weak evidence for the study hypothesis.

“BRCAX” refers breast cancers occurring in women with a family history predictive of being a BRCA1/2 mutation carrier, but BRCA1/2 genetic screening has failed to find causal mutations. In this study, we report the findings of the genetic architecture of BRCAX with novel and redefined candidate loci and their potential impacts on preventive strategy. We performed a genome-wide association study involving 1,469 BRCAX cases from the Korean Hereditary Breast Cancer study, and high-risk breast cancer cases (1,482 Asians and 9,902 Europeans) from the Breast Cancer Association Consortium. We also evaluated the previously reported susceptibility loci for their roles in the high-risk breast cancers. We have identified three novel loci (PDE7B, UBL3, and a new independent marker in CDKN2B-AS1) associated with BRCAX, and replicated previously reported SNPs (24 of 92) and moderate/high-penetrance (seven of 23) genes for Korean BRCAX. For the novel candidate loci, evidence supported their roles in regulatory function. We estimated that the common low-penetrance loci might explain a substantial part of high-risk breast cancer (39.4% for Koreans and 24.0% for Europeans). Our study findings suggest that common genetic markers with lower penetrance constitute a part of susceptibility to high-risk breast cancers, with potential implications for a more comprehensive genetic screening test.

Video Anomaly Detection(VAD) has been traditionally tackled in two main methodologies: the reconstruction-based approach and the prediction-based one. As the reconstruction-based methods learn to generalize the input image, the model merely learns an identity function and strongly causes the problem called generalizing issue. On the other hand, since the prediction-based ones learn to predict a future frame given several previous frames, they are less sensitive to the generalizing issue. However, it is still uncertain if the model can learn the spatio-temporal context of a video. Our intuition is that the understanding of the spatio-temporal context of a video plays a vital role in VAD as it provides precise information on how the appearance of an event in a video clip changes. Hence, to fully exploit the context information for anomaly detection in video circumstances, we designed the transformer model with three different contextual prediction streams: masked, whole and partial. By learning to predict the missing frames of consecutive normal frames, our model can effectively learn various normality patterns in the video, which leads to a high reconstruction error at the abnormal cases that are unsuitable to the learned context. To verify the effectiveness of our approach, we assess our model on the public benchmark datasets: USCD Pedestrian 2, CUHK Avenue and ShanghaiTech and evaluate the performance with the anomaly score metric of reconstruction error. The results demonstrate that our proposed approach achieves a competitive performance compared to the existing video anomaly detection methods.

Objectives: Statins are essential in the prevention of cardiovascular disease; however, their association with type 2 diabetes mellitus (T2DM) risk is concerning. We examined whether genetic susceptibility to T2DM modifies the association between regular statin use and T2DM risk.Methods: This study included 447 176 individuals from the UK Biobank without baseline diabetes or major cardiovascular disease. Statin use was recorded at baseline, and T2DM incidence was determined using clinical records. Polygenic risk scores (PRS) for T2DM risk were provided by the UK Biobank. Using propensity scores adjusted for age, sex, body mass index, and comorbidities, 14 831 statin users were matched with 37 060 non-users. Cox proportional hazards models were used to estimate the interaction effect of statin use and PRS on T2DM incidence, adjusting for key confounders.Results: In the propensity-matched cohort, 3675 of 51 891 participants developed T2DM over a mean follow-up period of 13.7 years. Within the top 5% of the PRS distribution, per 1000 person-years, the incidence of T2DM was 15.42 for statin users versus 12.18 for non-users. Among the lowest 5%, the incidence was 1.90 for statin users and 1.65 for non-users. Based on the Cox proportional hazards model, regular statin use was associated with a 1.24-fold increased T2DM risk (95% confidence interval [CI], 1.15 to 1.33). Furthermore, PRS exhibited a significant multiplicative interaction with regular statin use (odds ratio, 1.10; 95% CI, 1.02 to 1.19).Conclusions: PRS may help identify individuals particularly susceptible to the diabetogenic effects of statins, providing a potential path for personalized cardiovascular disease management.

The current human reference genome (GRCh38), with its superior quality, has contributed significantly to genome analysis. However, GRCh38 may still underrepresent the ethnic genome, specifically for Asians, though exactly what we are missing is still elusive. Here, we juxtaposed GRCh38 with a high-contiguity genome assembly of one Korean (AK1) to show that a part of AK1 genome is missing in GRCh38 and that the missing regions harbored ~1390 putative coding elements. Furthermore, we found that multiple populations shared some certain parts in the missing genome when we analyzed the “unmapped” (to GRCh38) reads of fourteen individuals (five East-Asians, four Europeans, and five Africans), amounting to ~5.3 Mb (~0.2% of AK1) of the total genomic regions. The recovered AK1 regions from the “unmapped reads”, which were the estimated missing regions that did not exist in GRCh38, harbored candidate coding elements. We verified that most of the common (shared by ≥7 individuals) missing regions exist in human and chimpanzee DNA. Moreover, we further identified the occurrence mechanism and ethnic heterogeneity as well as the presence of the common missing regions. This study illuminates a potential advantage of using a pangenome reference and brings up the need for further investigations on the various features of regions globally missed in GRCh38.