LRFN5 locus structure is associated with autism and influenced by the sex of the individual and locus conversions

Asian-European differentiation of schizophrenia-associated genes driven by admixture and natural selection

The European-centered genome-wide association studies of schizophrenia (SCZ) may not be well applied to non-European populations. We analyzed 1,592 reported SCZ-associated genes using the public genome data and found an overall higher Asian-European differentiation on the SCZ-associated variants than at the genome-wide level. Notable examples included 15 missense variants, a regulatory variant SLC5A10-rs1624825, and a damaging variant TSPAN18-rs1001292. Independent local adaptations in recent 25,000 years, after the Asian-European divergence, could have contributed to such genetic differentiation, as were identified at a missense mutation LTN1-rs57646126-A in Asians, and a non-risk allele ZSWIM6-rs72761442-G in Europeans. Altai-Neanderthal-derived alleles may have opposite effects on SCZ susceptibility between ancestries. Furthermore, adaptive introgression was detected on the non-risk haplotype at 1q21.2 in Europeans, while in Asians it was observed on the SCZ risk haplotype at 3p21.31 which is also potentially ultra-violet protective. This study emphasizes the importance of including more representative Asian samples in future SCZ studies.

Genome-scale copy number variant analysis in schizophrenia patients and controls from South India

Copy number variants (CNVs) are among the main genetic factors identified in schizophrenia (SZ) through genome-scale studies conducted mostly in Caucasian populations. However, to date, there have been no genome-scale CNV reports on patients from India. To address this shortcoming, we generated, for the first time, genome-scale CNV data for 168 SZ patients and 168 controls from South India. In total, 63 different CNVs were identified in 56 patients and 46 controls with a significantly higher proportion of medium-sized deletions (100 kb-1 Mb) after multiple testing (FDR = 2.7E-4) in patients. Of these, 13 CNVs were previously reported; however, when searched against GWAS, transcriptome, exome, and DNA methylation studies, another 17 CNVs with candidate genes were identified. Of the total 30 CNVs, 28 were present in 38 patients and 12 in 27 controls, indicating a significantly higher representation in the former (p = 1.87E-5). Only 4q35.1-q35.2 duplications were significant (p = 0.020) and observed in 11 controls and 2 patients. Among the others that are not significant, a few examples of patient-specific and previously reported CNVs include deletions of 11q14.1 (DLG2), 22q11.21, and 14q21.1 (LRFN5). 16p13.3 deletion (RBFOX1), 3p14.2 duplication (CADPS), and 7p11.2 duplication (CCT6A) were some of the novel CNVs containing candidate genes. However, these observations need to be replicated in a larger sample size. In conclusion, this report constitutes an important foundation for future CNV studies in a relatively unexplored population. In addition, the data indicate that there are advantages in using an integrated approach for better identification of candidate CNVs for SZ and other mental health disorders.

When 3D genome changes cause disease: the impact of structural variations in congenital disease and cancer

Large structural variations (SV) are a class of mutations that have long been known to cause a wide range of genetic diseases, from rare congenital disease to cancer. Many of these SVs do not directly disrupt disease-related genes and determining causal genotype-phenotype relationships has been challenging to disentangle in the past. This has started to change with our increased understanding of the 3D genome folding. The pathophysiologies of the different types of genetic diseases influence the type of SVs observed and their genetic consequences, and how these are connected to 3D genome folding. We propose guiding principles for interpreting disease-associated SVs based on our current understanding of 3D chromatin architecture and the gene-regulatory and physiological mechanisms disrupted in disease.

Potentially causal associations between placental DNA methylation and schizophrenia and other neuropsychiatric disorders

Increasing evidence supports the role of placenta in neurodevelopment and potentially, in the later onset of neuropsychiatric disorders. Recently, methylation quantitative trait loci (mQTL) and interaction QTL (iQTL) maps have proven useful to understand SNP-genome wide association study (GWAS) relationships, otherwise missed by conventional expression QTLs. In this context, we propose that part of the genetic predisposition to complex neuropsychiatric disorders acts through placental DNA methylation (DNAm). We constructed the first public placental cis-mQTL database including nearly eight million mQTLs calculated in 368 fetal placenta DNA samples from the INMA project, ran cell type- and gestational age-imQTL models and combined those data with the summary statistics of the largest GWAS on 10 neuropsychiatric disorders using Summary-based Mendelian Randomization (SMR) and colocalization. Finally, we evaluated the influence of the DNAm sites identified on placental gene expression in the RICHS cohort. We found that placental cis-mQTLs are highly enriched in placenta-specific active chromatin regions, and useful to map the etiology of neuropsychiatric disorders at prenatal stages. Specifically, part of the genetic burden for schizophrenia, bipolar disorder and major depressive disorder confers risk through placental DNAm. The potential causality of several of the observed associations is reinforced by secondary association signals identified in conditional analyses, regional pleiotropic methylation signals associated to the same disorder, and cell type-imQTLs, additionally associated to the expression levels of relevant immune genes in placenta. In conclusion, the genetic risk of several neuropsychiatric disorders could operate, at least in part, through DNAm and associated gene expression in placenta.

Abnormal Chromatin Folding in the Molecular Pathogenesis of Epilepsy and Autism Spectrum Disorder: a Meta-synthesis with Systematic Searching

How DNA is folded and packaged in nucleosomes is an essential regulator of gene expression. Abnormal patterns of chromatin folding are implicated in a wide range of diseases and disorders, including epilepsy and autism spectrum disorder (ASD). These disorders are thought to have a shared pathogenesis involving an imbalance in the number of excitatory-inhibitory neurons formed during neurodevelopment; however, the underlying pathological mechanism behind this imbalance is poorly understood. Studies are increasingly implicating abnormal chromatin folding in neural stem cells as one of the candidate pathological mechanisms, but no review has yet attempted to summarise the knowledge in this field. This meta-synthesis is a systematic search of all the articles on epilepsy, ASD, and chromatin folding. Its two main objectives were to determine to what extent abnormal chromatin folding is implicated in the pathogenesis of epilepsy and ASD, and secondly how abnormal chromatin folding leads to pathological disease processes. This search produced 22 relevant articles, which together strongly implicate abnormal chromatin folding in the pathogenesis of epilepsy and ASD. A range of mutations and chromosomal structural abnormalities lead to this effect, including single nucleotide polymorphisms, copy number variants, translocations and mutations in chromatin modifying. However, knowledge is much more limited into how abnormal chromatin organisation subsequently causes pathological disease processes, not yet showing, for example, whether it leads to abnormal excitation-inhibitory neuron imbalance in human brain organoids.

Integrative studies of 3D genome organization and chromatin structure

The structural organization of the genome is emerging as a crucial regulator of the cell state, affecting gene transcription, DNA replication, and repair. Over the last twenty years, increasing evidence prompted the development of new experimental techniques to study genome structure. In parallel with the complexity of the novel techniques, computational approaches have become an essential tool in any structural genomics laboratory to analyze and model the data. For biologists to be able to apply the most appropriate modeling approach, it is fundamental to understand the conceptual bases of distinct methods and the insights they can provide. Here, we will discuss recent advances that were possible thanks to 3D genome modeling, discuss their limitations and highlight future perspectives.