Paternal age, de novo mutation, and age at onset among co-affected schizophrenia sib-pairs: whole-genome sequencing in multiplex families
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Family-based genome-wide association study designs for increased power and robustness
Family-based genome-wide association studies (FGWASs) use random, within-family genetic variation to remove confounding from estimates of direct genetic effects (DGEs). Here we introduce a ‘unified estimator’ that includes individuals without genotyped relatives, unifying standard and FGWAS while increasing power for DGE estimation. We also introduce a ‘robust estimator’ that is not biased in structured and/or admixed populations. In an analysis of 19 phenotypes in the UK Biobank, the unified estimator in the White British subsample and the robust estimator (applied without ancestry restrictions) increased the effective sample size for DGEs by 46.9% to 106.5% and 10.3% to 21.0%, respectively, compared to using genetic differences between siblings. Polygenic predictors derived from the unified estimator demonstrated superior out-of-sample prediction ability compared to other family-based methods. We implemented the methods in the software package snipar in an efficient linear mixed model that accounts for sample relatedness and sibling shared environment.
Associations between common genetic variants and income provide insights about the socio-economic health gradient
We conducted a genome-wide association study on income among individuals of European descent (N = 668,288) to investigate the relationship between socio-economic status and health disparities. We identified 162 genomic loci associated with a common genetic factor underlying various income measures, all with small effect sizes (the Income Factor). Our polygenic index captures 1–5% of income variance, with only one fourth due to direct genetic effects. A phenome-wide association study using this index showed reduced risks for diseases including hypertension, obesity, type 2 diabetes, depression, asthma and back pain. The Income Factor had a substantial genetic correlation (0.92, s.e. = 0.006) with educational attainment. Accounting for the genetic overlap of educational attainment with income revealed that the remaining genetic signal was linked to better mental health but reduced physical health and increased risky behaviours such as drinking and smoking. These findings highlight the complex genetic influences on income and health.
Generation of live mice from haploid ESCs with germline-DMR deletions or switch
Genomic imprinting is required for sexual reproduction and embryonic development of mammals, in which, differentially methylated regions (DMRs) regulate the parent-specific monoallelic expression of imprinted genes. Numerous studies on imprinted genes have highlighted their critical roles in development. However, what imprinting network is essential for development is still unclear. Here, we establish a stepwise system to reconstruct a development-related imprinting network, in which diploid embryonic stem cells (ESCs) are derived by fusing between parthenogenetic (PG)- and androgenetic (AG)-haploid embryonic stem cells (haESCs) with different DMR deletions (termed Ha-Ha-fusion system), followed by tetraploid complementation to produce all-haESC fetuses. Diploid ESCs fused between PG-haESCs carrying 8 maternally-derived DMR deletions and AG-haESCs with 2 paternally-derived DMR deletions give rise to live pups efficiently, among which, one lives to weaning. Strikingly, diploid ESCs derived from the fusion of PG-haESCs with 7 maternal DMR deletions and AG-haESCs with 2 paternal DMR deletions and maternal Snrpn-DMR deletion also support full-term embryonic development. Moreover, embryos reconstructed by injection of AG-haESCs with hypomethylated H19-DMR into oocytes with H19-DMR deletion develop into live mice sustaining inverted allelic gene expression. Together, our findings indicate that restoration of monoallelic expression of 10 imprinted regions is adequate for the full-term development of all-haESC pups, and it works irrespective of their parental origins. Meanwhile, Ha-Ha-fusion system provides a useful tool for deciphering imprinting regulation networks during embryonic development.
Circular RNAs in neurological conditions – computational identification, functional validation, and potential clinical applications
Non-coding RNAs (ncRNAs) have gained significant attention in recent years due to advancements in biotechnology, particularly high-throughput total RNA sequencing. These developments have led to new understandings of non-coding biology, revealing that approximately 80% of non-coding regions in the genome possesses biochemical functionality. Among ncRNAs, circular RNAs (circRNAs), first identified in 1976, have emerged as a prominent research field. CircRNAs are abundant in most human cell types, evolutionary conserved, highly stable, and formed by back-splicing events which generate covalently closed ends. Notably, circRNAs exhibit high expression levels in neural tissue and perform diverse biochemical functions, including acting as molecular sponges for microRNAs, interacting with RNA-binding proteins to regulate their availability and activity, modulating transcription and splicing, and even translating into functional peptides in some cases. Recent advancements in computational and experimental methods have enhanced our ability to identify and validate circRNAs, providing valuable insights into their biological roles. This review focuses on recent developments in circRNA research as they related to neuropsychiatric and neurodegenerative conditions. We also explore their potential applications in clinical diagnostics, therapeutics, and future research directions. CircRNAs remain a relatively underexplored area of non-coding biology, particularly in the context of neurological disorders. However, emerging evidence supports their role as critical players in the etiology and molecular mechanisms of conditions such as schizophrenia, bipolar disorder, major depressive disorder, Alzheimer’s disease, and Parkinson’s disease. These findings suggest that circRNAs may provide a novel framework contributing to the molecular dysfunctions underpinning these complex neurological conditions.
Excess of rare noncoding variants in several type 2 diabetes candidate genes among Asian Indian families
Type 2 diabetes (T2D) etiology is highly complex due to its multiple roots of origin. Polygenic risk scores (PRS) based on genome-wide association studies (GWAS) can partially explain T2D risk. Asian Indian people have up to six times higher risk of developing T2D than European people, and underlying causes of this disparity are unknown.
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