The article "Weighted Burden Analysis of Rare Genetic Variants Identifies Novel Genes with Effects on BMI" [Hum Hered. 2025;90:72-81; https://doi.org/10.1159/000549644] by D. Curtis was published with the wrong open access license. The correct license of the article is CC-BY.The original article has been updated.

Introduction: High-mobility group box 1 (HMGB1) protein plays a significant role in cancer development and treatment response. The current research on the role of HMGB1 in lung cancer and its treatment outcomes is limited and inconsistent. This exploratory study investigated the association between HMGB1 common genetic variants and lung cancer susceptibility, as well as cisplatin chemotherapy response, in a Chinese cohort. Methods: The current study included 106 individuals diagnosed with lung cancer and 93 healthy subjects, all of whom were part of a Chinese population cohort. HMGB1 polymorphisms (rs1045411, rs1412125, rs2249825, and rs1360485) were genotyped using the TaqMan single-nucleotide polymorphism typing method. HMGB1 gene expression in the lung tissue of patients was quantified using real-time PCR. All patients were administered cisplatin, and their response to the drug was evaluated. All statistical analyses were performed using GraphPad Prism v10. Results: The control group exhibited a higher frequency of heterozygous variants for HMGB1 polymorphisms rs1045411 (p = 0.01, odds ratio [OR] = 0.45) and rs1412125 (p = 0.03, OR = 0.46) than the patients. Moreover, the combined mutant genotypes for HMGB1 rs1045411 (p = 0.0001, OR = 0.15) and rs2249825 (p = 0.003, OR = 0.19) exhibited favorable responses to cisplatin treatment. Moreover, the wild-type variants of rs1045411 and rs2249825 exhibited higher HMGB1 expression than the mutants; however, this difference was not statistically significant. Conclusion: This preliminary investigation indicated potential associations between HMGB1 genetic variants and lung cancer susceptibility and treatment response. These exploratory findings necessitate further validation through larger multicenter studies incorporating functional assays to elucidate the biological significance and clinical utility of HMGB1 polymorphisms in the management of lung cancer.

Karger Publishers and the editors of Human Heredity would like to thank the reviewers for their ongoing support in reviewing manuscripts for our Journal in 2025. This year we have chosen not to disclose the names of our reviewers to preserve the principle of anonymity inherent to the single-blind peer-review we follow. Even so, this should not be in our way to sincerely thank all contributing reviewers who have volunteered their time, effort, and expertise in benefit of the quality of the manuscripts we received and published in 2025. Individual reviewers can still claim their personal “Certificate of Review” via the Journal’s manuscript submission system.

Introduction: We show that generalizations of stable population (GSPM) and agent-based models (ABMs) are useful tools to simulate trajectories of human phenotypes. Although mathematically very different, both classes of models can simultaneously account for multiple determinants of the population distribution of a phenotype across time and space. These include genetic transmission, assortative mating, differential fertility, vertical and horizontal cultural heredity, gene-environments interactions (GxE), and environmental feedback. We propose an application to obesity, a condition that has spread rapidly around the globe, increasing the risk of adult chronic illnesses and mortality. Methods: We choose body mass index as the target phenotype, and formulate GSPM and ABMs that include genetic inheritance, GxE, assortative mating, and fertility differentials. We exclude, in this version, the role of vertical cultural heredity. The GSPM is built on time-varying stochastic matrices that trace the trajectory of the phenotype by groups. The ABM models the behavior of individual agents integrating a stochastic component modifying each agent’s behavior. Results: There are four key results. First, differential fertility dominates the phenotype’s time trajectory, followed by assortative mating and GxE. Second, contrary to research in other phenotypes, the impact of assortative mating cannot offset the influence of fertility differentials. Third, concerning the formal representation of the transmission process, we show that the use of simple Mendelian models to represent complex phenotypes can produce badly biased inferences. Fourth, despite their mathematical differences, the GSPM and ABM produce virtually identical results. Conclusions: Modeling phenotypes with complex genetic transmission and heavily dependent on regimes of fertility differentials, assortative mating and GxE ought not to rely on excessive simplifications, as has traditional been done in past research. Both, the GSPM and ABM are useful, accessible, and effective tools to introduce more realism in the modeling of these phenotypes, and can be used as guides for policy interventions.

Introduction: A previous study of 200,000 exome-sequenced UK Biobank participants investigating the association between rare coding variants and BMI had implicated two genes, MC4R and PCSK1, at exome-wide significance. In addition, further 66 genes were significant with an uncorrected p value of <0.001. Methods: Exome sequence data have become available for further 270,000 participants, and weighted burden analyses to test for association with BMI were carried out in this sample for all the 68 genes highlighted by the previous study. Results: Three novel genes, in addition to MC4R and PCSK1, were significant after correction for multiple testing: PTOV1, GALNT9, and ATP8B2. All five genes were exome-wide significant in the whole sample of 470,000 participants. Rare coding variants impairing gene function were associated with reduced BMI for ATP8B2 but increased BMI for the other genes, and for all genes, loss of function variants had larger effect sizes than nonsynonymous variants. Conclusion: The biological mechanisms whereby the novel genes might affect BMI are not clear, although impairment of ATP8B2 might possibly have an effect on insulin secretion. Functional studies might throw further light on how these genes are involved in regulation of body weight. Collectively, the identified variants are very rare and do not make a major contribution to variation in BMI in the population. This research has been conducted using the UK Biobank Resource.

Introduction: Asthma is a chronic respiratory disorder characterized by airway inflammation, hyperresponsiveness, and reversible airflow obstruction. Despite therapeutic strategies, asthma remains inadequately controlled in many patients. Genetic predisposition plays a significant role in asthma pathogenesis, and the proteinase-activated receptor 2 (PAR-2), encoded by the F2RL1 gene, has been associated with asthma. However, the role of PAR-2 and F2RL1 variants in the Chinese population remains unclear. This study aimed to investigate the relationship between common F2RL1 polymorphisms and PAR-2 expression and their association with asthma susceptibility and clinical severity in a Chinese population. Methods: This study enrolled 250 clinically diagnosed Chinese patients with asthma and matched healthy controls of a similar age and geographical region. Four single nucleotide polymorphisms in the F2RL1 gene (rs1529505, rs631465, rs2242991, and rs2243057) were genotyped using the TaqMan genotyping method. PAR-2 mRNA expression was quantified through real-time PCR in intravenous blood samples. Statistical analyses were conducted using GraphPad Prism v10 and other software. Results: Variants of the F2RL1 gene, specifically rs1529505 (odds ratio [OR] = 1.65, 95% confidence interval [CI] = 1.26–2.14, p = 0.0002) and rs2272991 (OR = 1.89, 95% CI = 1.32–2.71, p = 0.0005), were associated with asthma predisposition. Genetic variants rs1529505 and rs631465 were associated with susceptibility and clinical severity in Chinese patients with asthma. The mutant genotypes of rs2272991 and rs1529505 correlated with elevated PAR-2 mRNA expression levels. Haplotype distribution did not reveal significant differences between asthma cases and controls, nor among severity groups. Conclusion: This study elucidated the influence of F2RL1 polymorphisms on PAR-2 mRNA expression and their impact on asthma pathogenesis within the Chinese population. Further research involving diverse populations is necessary to validate these findings.

Introduction: A previous study has demonstrated the protective effect of NID1 on myocardial infarction. This study aimed to assess the correlation between NID1 polymorphisms and the prognosis of heart failure (HF). In this study, we aimed to evaluate the association of NID1 polymorphisms with HF. Methods: A total of 1,000 patients with HF were enrolled in the discovery cohort. Genotyping was conducted to assess the relationship between common variants in the NID1 gene and the prognosis of HF. A replication cohort involving 2,266 HF patients was used to validate the association between variants and the prognosis of HF. A series of function analysis were conducted to illuminate the underlying mechanism. Results: Synonymous variant rs3738530 was identified to be associated with the prognosis of HF in both the discovery cohort (adjusted p = 0.006, HR = 1.58, 95% CI = 1.14–2.19) and replication cohort (adjusted p = 0.005, HR = 1.83, 95% CI = 1.20–2.80). Western blot analysis demonstrated that the protein level of NID1 was significantly higher in the rs3738530-T allele compared to the A allele (p < 0.05). Transcription assays indicated that individuals with the rs3738530-AT+TT genotype exhibited elevated levels of NID1 mRNA relative to those with the AA genotype. Apoptosis assay indicated that overexpression of NID1 could protect AC16 cells from hypoxia/reoxygenation-induced apoptosis. Furthermore, patients with rs3738530-AT+TT genotype exhibited a higher left ventricular ejection fraction and decreased left ventricular end-diastolic diameter compared to those with rs3738530-AA genotype (p < 0.05). Conclusion: Common variant rs3738530 in the NID1 gene is associated with the prognosis of HF. NID1 may be a promising therapeutic target for HF in the future.

Introduction: The aim of this study was to explore the relationships between mitochondrial tRNA (mt-tRNA) mutations and essential hypertension (EH), and providing the valuable information for molecular diagnosis of EH. Methods: We reported here clinical, genetic and molecular characterizations of two Han Chinese pedigrees with maternally inherited EH. We first amplified the mitochondrial genomes of the matrilineal relatives with EH, furthermore, Sanger sequencing was used to screen mitochondrial DNA (mtDNA) mutations. Phylogenetic conservation, mt-tRNA structural analyses, as well as mitochondrial functional evaluations were performed to assess the potential pathogenicity of mtDNA mutations. Results: EH-1 and EH-2 pedigrees exhibited typically maternal transmission; analysis of mitochondrial genomes revealed the co-existence of tRNAGln 4386T>C mutation in both families. Moreover, members of EH-2 pedigree carried the tRNAAla 5601C>T mutation. The m.4386T>C and m.5601C>T mutations were very conserved and implicated to have impact on mitochondrial functions. Compared with the control cells and cells with only the m.4386T>C mutation, cells carrying both m.4386T>C and m.5601C>T mutations exhibited much lower levels of ATP, membrane potential and mtDNA copy number, whereas reactive oxygen species increased significantly. Thus, the m.5601C>T and m.4386T>C mutations caused mitochondrial dysfunctions and involved in EH progression. Conclusion: The m.5601C>T may be a secondary variant that increase the penetrance and expressivity of hypertension-associated tRNAGln 4386T>C mutation.

Introduction: Next-generation sequencing (NGS) data analysis has become an integral part of clinical genetic diagnosis, raising the question of variant prioritization. The Population Sampling Probability (PSAP) method has been developed to tackle the issue of variant prioritization in the exome of a single patient, by leveraging allele frequencies from population databases and a variant pathogenicity score. Methods: Here, we present Easy-PSAP, a completely new implementation of the PSAP method comprising two user-friendly and highly adaptable pipelines. Easy-PSAP allows the gene-based recalibration of any in silico pathogenicity prediction score compared to scores of variants seen in the general population, including popular scores like CADD or AlphaMissense. Easy-PSAP can evaluate genetic variants at the scale of a whole exome or a whole genome using information from the latest population and annotation databases. Results: Through simulations on synthetic disease exomes, we show that Easy-PSAP is able to rank more than 50% of causal pathogenic variants in the top 10 variants for an autosomal dominant model of transmission and in top 1 for an autosomal recessive model of transmission. Discussion: These findings, along with the accessibility of the pipeline to both researchers and clinicians, make Easy-PSAP a state-of-the-art tool for variant prioritization in NGS data that can continue to evolve as new frameworks and databases become available. Easy-PSAP is implemented in R and bash within an open-source Snakemake framework. It is available on GitHub alongside conda environments containing the required dependencies (https://github.com/msogloblinsky/Easy-PSAP).

Introduction: Rheumatoid arthritis (RA) has become a serious threat to human health and quality of life worldwide. Previous studies have demonstrated that genetic factors play a crucial role in the onset and progression of RA. Due to the rapid development of genome-wide association study (GWAS) and large-scale genetic analysis, GWAS research on RA has received widespread attention in recent years. Therefore, we conducted a comprehensive visualization and bibliometric analysis of publications to identify hotspots and future trends in GWAS research on RA. Methods: Literature on RA and GWAS published between 2002 and 2024 was extracted from the Web of Science Core Collection database by strategic screening. Collected data were further analyzed by using VOSviewer, CiteSpace, and Excel. The collaborations networks of countries, authors, institutions, and the co-citation networks of publications were visualized. Finally, research hotspots and fronts were examined. Results: A total of 713 publications with 45,773 citations were identified. The number of publications and citations has had a significant surge since 2007. The United States contributed the most publications globally. Okada, Yukinori, was the most influential author. The most productive institution in this field was the University of Manchester. The analysis of keywords revealed that “mendelian randomization analysis”, “association”, “innate”, “instruments”, “bias”, “pathogenesis”, and “genome-wide association study” are likely to be the frontiers of research in this field. Conclusion: This study can be used to predict future research advances in the fields of GWAS on RA and helps to promote academic collaboration among scholars.