Smokers tend to weigh less than never smokers, while successful quitting leads to an increase in body weight. Because smokers and non-smokers may differ in genetic and environmental family background, we analysed data from twin pairs in which the co-twins differed by their smoking behaviour to evaluate if the association between smoking and body mass index (BMI) remains after controlling for family background. The international CODATwins database includes information on smoking and BMI measured between 1960 and 2012 from 156,593 twin individuals 18–69 years of age. Individual-based data (230,378 measurements) and data of smoking discordant twin pairs (altogether 30,014 pairwise measurements, 36% from monozygotic [MZ] pairs) were analysed with linear fixed-effects regression models by 10-year periods. In MZ pairs, the smoking co-twin had, on average, 0.57 kg/m² lower BMI in men (95% confidence interval (CI): 0.49, 0.70) and 0.65 kg/m² lower BMI in women (95% CI: 0.52, 0.79) than the never smoking co-twin. Former smokers had 0.70 kg/m² higher BMI among men (95% CI: 0.63, 0.78) and 0.62 kg/m² higher BMI among women (95% CI: 0.51, 0.73) than their currently smoking MZ co-twins. Little difference in BMI was observed when comparing former smoking co-twins with their never smoking MZ co-twins (0.13 kg/m², 95% CI 0.04, 0.23 among men; -0.04 kg/m², 95% CI -0.16, 0.09 among women). The associations were similar within dizygotic pairs and when analysing twins as individuals. The observed series of cross-sectional associations were independent of sex, age, and measurement decade. Smoking is associated with lower BMI and smoking cessation with higher BMI. However, the net effect of smoking and subsequent cessation on weight development appears to be minimal, i.e. never more than an average of 0.7 kg/m².

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.

There is evidence that birth size is positively associated with height in later life, but it remains unclear whether this is explained by genetic factors or the intrauterine environment. To analyze the associations of birth weight, length and ponderal index with height from infancy through adulthood within mono- and dizygotic twin pairs, which provides insights into the role of genetic and environmental individual-specific factors. This study is based on the data from 28 twin cohorts in 17 countries. The pooled data included 41,852 complete twin pairs (55% monozygotic and 45% same-sex dizygotic) with information on birth weight and a total of 112,409 paired height measurements at ages ranging from 1 to 69 years. Birth length was available for 19,881 complete twin pairs, with a total of 72,692 paired height measurements. The association between birth size and later height was analyzed at both the individual and within-pair level by linear regression analyses. Within twin pairs, regression coefficients showed that a 1-kg increase in birth weight and a 1-cm increase in birth length were associated with 1.14-4.25 cm and 0.18-0.90 cm taller height, respectively. The magnitude of the associations was generally greater within dizygotic than within monozygotic twin pairs, and this difference between zygosities was more pronounced for birth length. Both genetic and individual-specific environmental factors play a role in the association between birth size and later height from infancy to adulthood, with a larger role for genetics in the association with birth length than with birth weight.

Extracellular vesicles (EVs) play an important role in cancer progression and metastasis. The increasing clinical proteomics data provides an opportunity to uncover new biomarkers and therapeutic targets in cancer specific EVs. Here, we present an integrated data analysis approach that leverages a comprehensive protein catalog from EVs, blood plasma, and the cancer cell surface to identify EV‐associated proteins and evaluate their potential as therapeutic targets in cancer cells. Quantitative proteomics data from 12 cancer types ( n = 2,272) identified 3,250 proteins that are commonly found in EV studies and EV quantity data. Receptor kinases (RKs) are crucial in cancer signalling pathways and have been widely studied targets. Our analysis focused on identifying RKs with significant high expression in cancer types that were also detected in EVs. Notably, PTK7 emerged as a significant target with high expression or survival association in seven independent cancer cohorts. We then explored the druggability of the RKs. Our analysis of drug repurposing network and RNAi screening suggested PTK7 as a potential therapeutic target with no FDA approved drugs in cancer. Overall, this integrative analysis proposes a framework to prioritize EV‐associated candidates for downstream therapeutic investigation in cancer.

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.

Studies have shown that the current human reference genome (GRCh38) might miss information for some populations, but “exactly what we miss” is still elusive due to the lower contiguity of non-reference genomes. We juxtaposed the GRCh38 with high contiguity genome assemblies, AK1, to show that ∼1.8% (∼53.4 Mbp) of AK1 sequences missed in GRCh38 with ∼0.76% (∼22.2 Mbp) of ectopic chromosomes. The unique AK1 sequences harbored ∼1,390 putative coding elements. We found that ∼5.3Mb (∼0.2%) of the AK1 sequences aligned and recovered the “unmapped” reads of fourteen individuals (5 East-Asians, 4 Europeans, and 5 Africans) as a reference. The regions that “unmapped” reads aligned included 110 common (shared between ≥2 individuals) and 38 globally (≥7 individuals) missing regions with 25 candidate coding elements. We verified that many of the common missing regions exist in multiple populations and chimpanzee’s DNA. Our study illuminates not only the discovery of missing information but the use of highly precise ethnic genomes in understanding human genetics.