HGG Advances最新文献

Ribosomes are ribonucleoproteins that are responsible for protein synthesis. They consist of ribosomal proteins and ribosomal RNAs (rRNAs). Pre-rRNAs are co-transcriptionally processed and chemically modified. The 2'-O-methylation of rRNAs is guided by box C/D small nucleolar ribonucleoprotein particles (snoRNPs), which are composed of a box C/D snoRNA and the core proteins NOP56, NOP58, SNU13, and the methyltransferase fibrillarin. Catalytically active box C/D snoRNPs function in nucleoli. We performed trio whole-exome sequencing in a proband with a severe neurodevelopmental disorder including global developmental delay, microcephaly, seizures, and ophthalmological and brain abnormalities and his healthy parents and identified the homozygous synonymous variant c.516G>A; p.Leu172= in NOP58. In fibroblasts of the proband, we demonstrated skipping of exon 7 in most NOP58 mRNAs, while ∼20% canonically spliced NOP58 transcripts were detected in the proband compared with control cells. NOP58 protein levels were reduced to ∼12% in proband cells that concomitantly reduced fibrillarin levels. Analysis of nucleoli in proband-derived fibroblasts revealed changes in the number of nucleolar condensates and in nucleolar morphology. We found reduced levels of three box C/D snoRNAs required for 2'-O-methylation and of one box C/D snoRNA important for 2'-O-methylation and pre-rRNA processing. Analysis of pre-rRNA maturation by RT-qPCR revealed increased 45S and 21S pre-rRNA levels, whereas the amplification signal for the 47S, 32S, and 26S pre-rRNAs was substantially decreased in proband compared with control cells. Together, our data unveil that the homozygous NOP58 variant c.516G>A represents a hypomorphic allele and underlies the neurodevelopmental phenotype in the proband, likely by impairing pre-rRNA maturation.

Large biobanks, including the Million Veteran Program (MVP), the UK Biobank, and FinnGen, provide genetic association results for more than 1 million individuals for hundreds of phenotypes. To select targets for pharmaceutical development, as well as to improve the understanding of existing targets, we harmonized these studies and performed two-sample Mendelian randomization (MR) on 2,003 phenotypes using genetic variants associated with gene expression (derived from GTEx and eQTLGen) and plasma protein levels (derived from ARIC, Fenland, and deCODE) as proxies of target modulation. We found 69,669 gene-trait pairs with evidence (p ≤ 1.6 × 10^-9) for causal effects. From the selected gene-trait pairs, we observed 6,447 genes with strong causal evidence for at least one of 2,003 investigated traits. As expected, being identified as a gene-trait pair in our approach was significantly associated with higher odds of being an approved drug target and indication. We were able to rediscover 9% of approved drug targets in ChEMBL 34. Moreover, identified gene-traits were significantly associated with higher odds of being previously described as a gene-trait pair in OMIM, ClinVar, mouse knockout data, and rare variant burden studies. To enhance the translational potential of the resource, we developed a predictive ranking model trained using approved drug targets described in ChEMBL 34 as well as several different biological annotations. This model was able to accurately predict the odds of a particular significant MR result being developed into an approved drug and its clinical indication (precision-recall area under the receiver operating characteristic curve 0.79). We make our results publicly available in CIPHER.

Oxidative stress has been implicated in Parkinson disease (PD). Genes involved in PD, such as PRKN, PINK1, and PARK7, contribute to oxidative stress in dopaminergic neurons. The X-linked G6PD gene encodes glucose 6-phosphate dehydrogenase, an important regulator of oxidative stress. Recent studies suggested that alpha-synuclein aggregates may impair G6PD activity and contribute to dopaminergic neuron loss, and that G6PD mutations may independently increase the risk of PD. In this study, we aimed to examine the role of common and rare G6PD variants in PD across 6 cohorts, including 8,905 PD cases, 16,770 proxy cases, and 394,098 controls. These cohorts were analyzed after stratification by sex and then combined to account for the G6PD X-linked location. Using logistic regression, we did not identify significant associations for common variants in any of the cohorts. The optimized sequence Kernel association (SKAT-O) test was performed to assess the effect of rare variants (minor allele frequency <0.01) across six cohorts, followed by a meta-analysis using metaSKAT, also demonstrating lack of association. In conclusion, we did not find evidence for a role for G6PD in PD.

Depression is a frequent focus of interest in genetic testing. Despite the growing availability of polygenic risk scores (PRSs) for depression, little is known about the psychological impact of receiving them in real-world settings. To quantify the impact of receiving an at-risk depression PRS result on depression and anxiety symptoms, we conducted a longitudinal, prospective cohort study of 23andMe research participants. Eligible participants were US residents 18 years old and older who completed two surveys between October 19, 2022 and October 9, 2023 assessing depression and anxiety symptoms and who had an at-risk PRS for depression (odds ratio ≥1.5). We compared 361 individuals who viewed their result with 556 who did not. Primary outcomes were changes in depression (Patient Health Questionnaire-8) and anxiety (Depression Anxiety Stress Scale-21) symptom scores relative to baseline. We fitted linear regressions to model each outcome, adjusting for age, sex, ancestry, income, prior depression and/or anxiety, and baseline scores. Using an equivalence testing framework, the smallest effect size of interest was defined as Cohen's d = ±0.5. Score changes from baseline to follow-up were statistically equivalent for individuals who viewed results and those who did not (adjusted between-group differences in score changes: depression, -0.17 points [90% confidence interval {CI} -0.59 to 0.24]; anxiety, -0.092 points [90% CI -0.35 to 0.17]; all p < 0.001). Results were consistent in substrata with or without prior depression or anxiety. We conclude that among genetically at-risk individuals, exposure to a depression PRS result was well tolerated in a real-world setting.

Clinical interest in polygenic (PRS) and integrated (PRS plus clinical factors) risk scores (IRS) is growing, yet little data exist on how healthcare providers navigate returning these results to patients. The eMERGE IV study implemented a genome-informed risk assessment for 11 common complex conditions, incorporating PRS, IRS, and monogenic findings, offering an opportunity to examine providers' experiences disclosing these results. We used a cross-sectional survey with closed- and open-ended questions to assess result disclosure experiences. All study providers involved in disclosing high-risk results were invited to participate. Of 21 respondents, 86% were female and the mean age was 35 years. Most were genetic counselors (76%), followed by pharmacists (10%), research coordinators (10%), and a nurse/nurse practitioner (5%). Confidence in disclosing high-risk results was highest for monogenic (92% extremely/very confident), followed by PRS (78%) and IRS (69%). Most rated disclosures as slightly/moderately complex (77% monogenic, 89% PRS, 69% IRS). Breast cancer (69%) and obesity (39%) were rated as the most challenging conditions to disclose. Key considerations when delivering PRS/IRS included clarifying clinical meaning, clear communication of risk, and acknowledging limitations. Challenges involved ensuring patient understanding, confusion over care recommendations, and PRS complexity. Concerns reflected both personal and perceived patient views, including PRS validity, interpretation of relative risk, and healthcare impact. Study findings provide early insights into result disclosure practices for different types of genomic risk and conditions, which can inform training, resources, and clinical integration of these emerging genomic tools.

Despite considerable advances in identifying risk factors for obesity, gaps remain in our understanding about its etiology. Genetic variants explain only a small portion of variation in obesity-related traits such as body mass index (BMI). Epigenetic regulation, which controls gene expression and is influenced by environmental and genetic factors, may account for additional variability in BMI. Epigenetic studies of BMI have largely been conducted in European ancestry populations, despite the disproportionate burden of obesity in African Americans (AAs). We conducted a sex-stratified BMI epigenome-wide association study meta-analysis in AA participants from the Jackson Heart Study (n = 1,604) and the Multi-Ethnic Study of Atherosclerosis (n = 179) with Illumina EPIC (850,000) array data. Linear regression models with methylation as the outcome and continuous BMI as the predictor were stratified by study and sex and meta-analyzed. We identified 208 methylation sites (CpGs, p < 8.72 × 10^-8) significantly associated with BMI; 151 had not been previously reported in the literature. Replication was performed in a separate sample of AA participants with 450,000 array data, which lacks many CpGs present in the 850,000 array. Replication testing was possible for only 29 of the 151 CpGs; 19 were statistically significant (p < 1.72 × 10^-3). Sex-specific results showed 4 female-only and 3 male-only BMI-CpGs not identified in the sex-combined results. Differentially methylated region (DMR) analysis resulted in 66 DMRs, including several regions near genes previously implicated for obesity (e.g., SOCS3, TGFB1). Further analyses showed enrichment of genes and traits related to the immune system and inflammation-related pathways (e.g., the IL-6/JAK/STAT pathway).

Venous thromboembolism (VTE) is a major cause of mortality, influenced by genetic and environmental factors. von Willebrand factor (VWF) mediates hemostasis by promoting platelet adhesion, and its plasma levels are associated with thrombotic risk. Although many non-coding variants in ABO are associated with VWF levels, VTE risk, and COVID-19 severity, the mechanisms underlying these associations remain unclear. In this study, we identified the ABO locus as the genomic region with the highest concentration of variants associated with VWF levels. Chromatin conformation analyses in endothelial cells revealed non-coding ABO variants (rs657152, rs9411377, rs660340, and rs505922) associated with VWF levels, VTE risk, and COVID-19 severity, located in spatial proximity to ADAMTS13. ADAMTS13 is a key regulator of VWF activity, and both ADAMTS13 and VWF play crucial roles in coagulation and thrombosis. Chromatin activation (CRISPRa) of the region near the non-coding ABO variant rs657152 increased ADAMTS13 transcription in endothelial cells, suggesting that this variant resides in a regulatory region with the potential to modulate long-range transcriptional control of ADAMTS13. Luciferase assay revealed reduced transcriptional activity driven by the rs505922-C allele in endothelial cells. These findings provide insights into the spatial organization of the ABO locus and its potential role in ADAMTS13 regulation.

Polygenic scores (PGSs) have shown promise in advancing precision medicine by capturing the additive effects of common genetic variants to assess inherited disease risk. However, their predictive accuracy remains limited in non-European populations. We enhanced our previously developed Bayesian polygenic model, "select and shrink with summary statistics" (S4), by introducing a multi-ancestry extension (S4-Multi) to improve prediction accuracy across African, American, East Asian, European, and South Asian ancestries. By leveraging simulated data and biobank cohorts from UK Biobank, FinnGen, Biobank Japan, the All of Us Research Program, and the Global Biobank Meta-Analysis Initiative, we benchmarked S4-Multi against leading methods for predicting type 2 diabetes, breast cancer, colorectal cancer, asthma, and stroke. In simulation tests, S4-Multi outperformed its single-ancestry version, achieving over 1.6 times greater accuracy in non-European populations, and matched or exceeded top-performing methods across all tested ancestry groups. In biobank tests, S4-Multi matched the performance of the best methods, varying by ancestry and phenotype. We find that S4-Multi achieves comparable performance using 9%-77% fewer genetic variants than competing models, highlighting potential for robust performance in clinical settings with limited available genomic data.

Despite advancements in genomics, misconceptions about the extent to which genetics contributes to observable differences across racial groups persist. These misconceptions are often rooted in genetic essentialism, a social-cognitive bias that leads individuals to believe that most complex traits are primarily determined by genetics. This scientifically inaccurate belief overlooks the environmental and social influences on complex human outcomes, reinforcing deterministic views about human diversity. Our study examines how and for whom genetics education can reduce genetic essentialist beliefs using targeted interventions. We use data from a randomized controlled trial collected at a large US West Coast public university in 2023, including 2,061 undergraduate students. Participants were randomly assigned to one of four curriculum-based interventions, ensuring balanced characteristics across conditions. Three interventions were compared: population thinking; multifactorial causation; and a curriculum where we combined both approaches, which we call full Humane Genetics Curriculum. Results are reported relative to a control group that taught students about climate change. Using structural equation modeling, we explore the effectiveness of these interventions with our data. We find that all three interventions reduce genetic essentialist beliefs by decreasing the perception of between-group racial variation and by reducing genetic attributions for complex human traits. We also find that the three intervention curricula are highly effective across sociodemographic group characteristics such as self-reported gender, self-reported race, and cultural/political belief systems. However, the interventions were more effective among students who possessed greater baseline genetics knowledge. Using these findings, we offer evidence-based strategies for curriculum development.

Chromosomal microarray analysis (CMA) detects pathogenic copy-number variants (pCNVs) and regions of homozygosity (ROHs) in prenatal genetic analysis. This study evaluates the clinical significance of ROH detection in prenatal settings. We reviewed 178 fetuses with ROH detected by CMA among 20,546 fetuses from 2015 to 2023. Clinical and laboratory results, including ultrasound anomalies, cell-free DNA (cfDNA) screening, karyotyping, exome sequencing (ES), and methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA), were analyzed. These 178 fetuses with ROH accounted for 0.87% of prenatal cases. Among them, 24.2% had positive cfDNA screening results, and 52.8% underwent follow-up ES, trio CMA, and MS-MLPA. Follow-up studies detected pathogenic homozygous variants within ROH in two fetuses and uniparental disomy (UPD)-related diseases in five fetuses. Our results and findings from the other five large prenatal case series from literature indicated that ROH detection in prenatal CMA has a baseline positive predictive value of 2.7% for autosomal-recessive disorders, 9.6% for UPD-related diseases, and 0.04% overall additive diagnostic yield. These findings support the use of ES and MS-MLPA for follow-up testing and provide guidance for genetic counseling in fetuses with ROH.