American journal of human genetics最新文献

Autism spectrum disorder (ASD) exhibits an ∼4:1 male-to-female sex bias and is characterized by early-onset impairment of social/communication skills, restricted interests, and stereotyped behaviors. Disruption of the Xp22.11 locus has been associated with ASD in males. This locus includes the three-exon PTCHD1, an adjacent multi-isoform long noncoding RNA (lncRNA) named PTCHD1-AS (spanning ∼1 Mb), and a poorly characterized single-exon RNA helicase named DDX53 that is intronic to PTCHD1-AS. While the relationship between PTCHD1/PTCHD1-AS and ASD is being studied, the role of DDX53 has not been comprehensively examined, in part because there is no apparent functional murine ortholog. Through clinical testing, here, we identified 8 males and 2 females with ASD from 8 unrelated families carrying rare, predicted damaging or loss-of-function variants in DDX53. Additionally, we identified a family consisting of a male proband and his affected mother with high-functioning autism, both harboring a gene deletion involving DDX53 and exons of the noncoding RNA PTCHD1-AS. Then, we examined databases, including the Autism Speaks MSSNG and Simons Foundation Autism Research Initiative, as well as population controls. We identified 26 additional individuals with ASD harboring 19 mostly maternally inherited, rare, damaging DDX53 variations, including two variants detected in families from the original clinical analysis. Our findings in humans support a direct link between DDX53 and ASD, which will be important in clinical genetic testing. These same autism-related findings, coupled with the observation that a functional orthologous gene is not found in mice, may also influence the design and interpretation of murine modeling of ASD.

Available large-scale genome-wide association study (GWAS) summary datasets predominantly stem from European populations, while sample sizes for other ethnicities, notably Central/South Asian, East Asian, African, Hispanic, etc., remain comparatively limited, resulting in low precision of causal effect estimations within these ethnicities when using Mendelian randomization (MR). In this paper, we propose a trans-ethnic MR method, TEMR, to improve the statistical power and estimation precision of MR in a target population that is underrepresented, using trans-ethnic large-scale GWAS summary datasets. TEMR incorporates trans-ethnic genetic correlation coefficients through a conditional likelihood-based inference framework, producing calibrated p values with substantially improved MR power. In the simulation study, compared with other existing MR methods, TEMR exhibited superior precision and statistical power in causal effect estimation within the target populations. Finally, we applied TEMR to infer causal relationships between concentrations of 16 blood biomarkers and the risk of developing five diseases (hypertension, ischemic stroke, type 2 diabetes, schizophrenia, and major depression disorder) in East Asian, African, and Hispanic/Latino populations, leveraging biobank-scale GWAS summary data obtained from individuals of European descent. We found that the causal biomarkers were mostly validated by previous MR methods, and we also discovered 17 causal relationships that were not identified using previously published MR methods.

We introduce a sizable (n = 34) whole-genome dataset on Armenians, a population inhabiting the region in West Asia known as the Armenian highlands. Equipped with this genetic data, we conducted a whole-genome study of Armenians and deciphered their fine-scale population structure and complex demographic history. We demonstrated that the Armenian populations from western, central, and eastern parts of the highlands are relatively homogeneous. The Sasun, a population in the south that had been argued to have received a major genetic contribution from Assyrians, was instead shown to have derived its slightly divergent genetic profile from a bottleneck that occurred in the recent past. We also investigated the debated question on the genetic origin of Armenians and failed to find any significant support for historical suggestions by Herodotus of their Balkan-related ancestry. We checked the degree of continuity of modern Armenians with ancient inhabitants of the eastern Armenian highlands and detected a genetic input into the region from a source linked to Neolithic Levantine Farmers at some point after the Early Bronze Age. Additionally, we cataloged an abundance of new mutations unique to the population, including a missense mutation predicted to cause familial Mediterranean fever, an autoinflammatory disorder highly prevalent in Armenians. Thus, we highlight the importance of further genetic and medical studies of this population.

Autism spectrum disorder (ASD) displays a notable male bias in prevalence. Research into rare (<0.1) genetic variants on the X chromosome has implicated over 20 genes in ASD pathogenesis, such as MECP2, DDX3X, and DMD. The "female protective effect" in ASD suggests that females may require a higher genetic burden to manifest symptoms similar to those in males, yet the mechanisms remain unclear. Despite technological advances in genomics, the complexity of the biological nature of sex chromosomes leaves them underrepresented in genome-wide studies. Here, we conducted an X-chromosome-wide association study (XWAS) using whole-genome sequencing data from 6,873 individuals with ASD (82% males) across Autism Speaks MSSNG, Simons Simplex Collection (SSC), and Simons Powering Autism Research (SPARK), alongside 8,981 population controls (43% males). We analyzed 418,652 X chromosome variants, identifying 59 associated with ASD (p values 7.9 × 10^-6 to 1.51 × 10^-5), surpassing Bonferroni-corrected thresholds. Key findings include significant regions on Xp22.2 (lead SNP rs12687599, p = 3.57 × 10^-7) harboring ASB9/ASB11 and another encompassing DDX53 and the PTCHD1-AS long non-coding RNA (lead SNP rs5926125, p = 9.47 × 10^-6). When mapping genes within 10 kb of the 59 most significantly associated SNPs, 91 genes were found, 17 of which yielded association with ASD (GRPR, AP1S2, DDX53, HDAC8, PCDH19, PTCHD1, PCDH11X, PTCHD1-AS, DMD, SYAP1, CNKSR2, GLRA2, OFD1, CDKL5, GPRASP2, NXF5, and SH3KBP1). FGF13 emerged as an X-linked ASD candidate gene, highlighted by sex-specific differences in minor allele frequencies. These results reveal significant insights into X chromosome biology in ASD, confirming and nominating genes and pathways for further investigation.

Cancer incidence and mortality differ among individuals of different ages, but the functional consequences of genetic alterations remain largely unknown. We systematically characterized genetic alterations within protein domains stratified by affected individual's age and showed that the mutational effects on domains varied with age. We further identified potential age-associated driver genes with hotspots across 33 cancers. The candidate drivers involved numerous cancer-related genes that participate in various oncogenic pathways and play central roles in human protein-protein interaction (PPI) networks. We found widespread age biases in protein domains and identified the associations between hotspots and age. Age-stratified PPI networks perturbed by hotspots were constructed to illustrate the function of mutations enriched in domains. We found that hotspots in young adults were associated with premature senescence. In summary, we provided a catalog of age-associated hotspots and their perturbed networks, which may facilitate precision diagnostics and treatments for cancer.

Exploring the molecular correlates of metabolic health measures may identify their shared and unique biological processes and pathways. Molecular proxies of these traits may also provide a more objective approach to their measurement. Here, DNA methylation (DNAm) data were used in epigenome-wide association studies (EWASs) and for training epigenetic scores (EpiScores) of six metabolic traits: body mass index (BMI), body fat percentage, waist-hip ratio, and blood-based measures of glucose, high-density lipoprotein cholesterol, and total cholesterol in >17,000 volunteers from the Generation Scotland (GS) cohort. We observed a maximum of 12,033 significant findings (p < 3.6 × 10^-8) for BMI in a marginal linear regression EWAS. By contrast, a joint and conditional Bayesian penalized regression approach yielded 27 high-confidence associations with BMI. EpiScores trained in GS performed well in both Scottish and Singaporean test cohorts (Lothian Birth Cohort 1936 [LBC1936] and Health for Life in Singapore [HELIOS]). The EpiScores for BMI and total cholesterol performed best in HELIOS, explaining 20.8% and 7.1% of the variance in the measured traits, respectively. The corresponding results in LBC1936 were 14.4% and 3.2%, respectively. Differences were observed in HELIOS for body fat, where the EpiScore explained ∼9% of the variance in Chinese and Malay -subgroups but ∼3% in the Indian subgroup. The EpiScores also correlated with cognitive function in LBC1936 (standardized β_range: 0.08-0.12, false discovery rate p [p_FDR] < 0.05). Accounting for the correlation structure across the methylome can vastly affect the number of lead findings in EWASs. The EpiScores of metabolic traits are broadly applicable across populations and can reflect differences in cognition.

Each human genome has approximately 5 million DNA variants. Even for complete loss-of-function variants causing inherited, monogenic diseases, current understanding based on gene-specific molecular function does not adequately predict variability observed between people with identical mutations or fluctuating disease trajectories. We present a parallel paradigm for loss-of-function variants based on broader consequences to the cell when aberrant polypeptide chains of amino acids are translated from mutant RNA to generate mutated proteins. Missense variants that modify primary amino acid sequence, and nonsense/frameshift variants that generate premature termination codons (PTCs), are placed in context alongside emergent themes of chaperone binding, protein quality control capacity, and cellular adaptation to stress. Relatively stable proteostasis burdens are contrasted with rapid changes after induction of gene expression, or stress responses that suppress nonsense mediated decay (NMD) leading to higher PTC transcript levels where mutant proteins can augment cellular stress. For known disease-causal mutations, an adjunctive variant categorization system enhances clinical predictive power and precision therapeutic opportunities. Additionally, with typically more than 100 nonsense and frameshift variants, and ∼10,000 missense variants per human DNA, the paradigm focuses attention on all protein-coding DNA variants, and their potential contributions to multimorbid states beyond classically designated inherited diseases. Experimental testing in clinically relevant systems is encouraged to augment current atlases of protein expression at single-cell resolution, and high-throughput experimental data and deep-learning models that predict which amino acid substitutions generate enhanced degradative burdens. Incorporating additional dimensions such as pan-proteome competition for chaperones, and age-related loss of proteostasis capacity, should further accelerate health impacts.

Central obesity is associated with higher risk of developing a wide range of diseases independent of overall obesity. Genome-wide association studies (GWASs) have identified more than 300 susceptibility loci associated with central obesity. However, the functional understanding of these loci is limited by the fact that most loci are in non-coding regions. To address this issue, our study first prioritized 2,034 single-nucleotide polymorphisms (SNPs) based on fine-mapping and epigenomic annotation analysis. Subsequently, we employed self-transcribing active regulatory region sequencing (STARR-seq) to systematically evaluate the enhancer activity of these prioritized SNPs. The resulting data analysis identified 141 SNPs with allelic enhancer activity. Further analysis of allelic transcription factor (TF) binding prioritized 20 key TFs mediating the central-obesity-relevant genetic regulatory network. Finally, as an example, we illustrate the molecular mechanisms of how rs8079062 acts as an allele-specific enhancer to regulate the expression of its targeted RNF157. We also evaluated the role of RNF157 in the adipogenic differentiation process. In conclusion, our results provide an important resource for understanding the genetic regulatory mechanisms underlying central obesity.