Role of miRNA binding site SNPs in candidate genes in a North Indian schizophrenia cohort

Schizophrenia (SZ) is a debilitating neuropsychiatric disorder with ~80% heritability. Despite several genetic studies including linkage and candidate gene association and more recently GWAS, which have identified several risk variants, the total heritability of SZ remains elusive. In addition, a number of gene expression studies have reported dysregulation of candidate genes both in brain and blood of SZ cases compared to controls. Although, the role of coding, promoter, intergenic and UTR SNPs, have been demonstrated, very little is known about the role of miRNA binding site SNPs. In this study, we undertook to investigate the association, if any, of this important class of regulatory variants with SZ. Using in silico prediction tools, 27 functionally relevant SNPs from around 150 candidate genes were prioritized and genotyped in a north Indian SZ cohort (n=507 cases; n=522 controls).\ud \ud Test of association of these SNPs showed only one variant rs7430 in PPP3CC to be associated (p=0.01) with SZ. Analysis of genotype data in a subset of patients (TD positive n=89; TD negative n=160) with Tardive dyskinesia (TD), an iatrogenic disorder of SZ, showed association of rs4846049 in MTHFR (p=0.04) & rs17881908 in GCLM (p= 0.05 ) with this condition. Further regression analysis of the genotype data with neurocognitive measures in a subset (cases n=152; controls n=290) of the study cohort, showed significant association of nine SNPs (p< 0.05) with different domains of cognition. Based on this moderately powered study, the contribution of miRNA binding site SNPs in candidate genes to SZ and to TD seems negligible. However, their promising contribution to cognitive parameters warrants additional investigations

Genetic Overlap Profiles of Cognitive Ability in Psychotic and Affective Illnesses: A Multisite Study of Multiplex Pedigrees

Background: Cognitive impairment is a key feature of psychiatric illness, making cognition an important tool for exploring of the genetics of illness risk. It remains unclear which measures should be prioritized in pleiotropy-guided research. Here, we generate profiles of genetic overlap between psychotic and affective disorders and cognitive measures in Caucasian and Hispanic groups. Methods: Data were from 4 samples of extended pedigrees (N = 3046). Coefficient of relationship analyses were used to estimate genetic overlap between illness risk and cognitive ability. Results were meta-analyzed. Results: Psychosis was characterized by cognitive impairments on all measures with a generalized profile of genetic overlap. General cognitive ability shared greatest genetic overlap with psychosis risk (average endophenotype ranking value [ERV] across samples from a random-effects meta-analysis = 0.32), followed by verbal memory (ERV = 0.24), executive function (ERV = 0.22), and working memory (ERV = 0.21). For bipolar disorder, there was genetic overlap with processing speed (ERV = 0.05) and verbal memory (ERV = 0.11), but these were confined to select samples. Major depressive disorder was characterized by enhanced working and face memory performance, as reflected in significant genetic overlap in 2 samples. Conclusions: There is substantial genetic overlap between risk for psychosis and a range of cognitive abilities (including general intelligence). Most of these effects are largely stable across of ascertainment strategy and ethnicity. Genetic overlap between affective disorders and cognition, on the other hand, tends to be specific to ascertainment strategy, ethnicity, and cognitive test battery

Dissecting the Shared Genetic Architecture Between Alzheimer’s Disease and Frailty: A Cross-Trait Meta-Analyses of Genome-Wide Association Studies

Introduction: Frailty is the most common medical condition affecting the aging population, and its prevalence increases in the population aged 65 or more. Frailty is commonly diagnosed using the frailty index (FI) or frailty phenotype (FP) assessments. Observational studies have indicated the association of frailty with Alzheimer’s disease (AD). However, the shared genetic and biological mechanism of these comorbidity has not been studied. Methods: To assess the genetic relationship between AD and frailty, we examined it at single nucleotide polymorphism (SNP), gene, and pathway levels. Results: Overall, 16 genome-wide significant loci (15 unique loci) (p meta-analysis \u3c 5 × 10−8) and 22 genes (21 unique genes) were identified between AD and frailty using cross-trait meta-analysis. The 8 shared loci implicated 11 genes: CLRN1-AS1, CRHR1, FERMT2, GRK4, LINC01929, LRFN2, MADD, RP11-368P15.1, RP11-166N6.2, RNA5SP459, and ZNF652 between AD and FI, and 8 shared loci between AD and FFS implicated 11 genes: AFF3, C1QTNF4, CLEC16A, FAM180B, FBXL19, GRK4, LINC01104, MAD1L1, RGS12, ZDHHC5, and ZNF521. The loci 4p16.3 (GRK4) was identified in both meta-analyses. The colocalization analysis supported the results of our meta-analysis in these loci. The gene-based analysis revealed 80 genes between AD and frailty, and 4 genes were initially identified in our meta-analyses: C1QTNF4, CRHR1, MAD1L1, and RGS12. The pathway analysis showed enrichment for lipoprotein particle plasma, amyloid fibril formation, protein kinase regulator, and tau protein binding. Conclusion: Overall, our results provide new insights into the genetics of AD and frailty, suggesting the existence of non-causal shared genetic mechanisms between these conditions

Classification of Schizophrenia, Bipolar Disorder and Major Depressive Disorder With Comorbid Traits and Deep Learning Algorithms

Many psychiatric disorders share genetic liabilities, but whether these shared liabilities can be utilized to classify and differentiate psychiatric disorders remains unclear. In this study, we use polygenic risk scores (PRSs) of 42 traits comorbid with schizophrenia (SCZ), bipolar disorder (BIP), and major depressive disorder (MDD) to evaluate their utilities. We found that combining target specific PRS with PRSs of comorbid traits can improve the classification of the target disorders. Importantly, without inclusion of PRSs from targeted disorders, we can still classify SCZ (accuracy 0.710 ± 0.008, AUC 0.789 ± 0.011), BIP (accuracy 0.782 ± 0.006, AUC 0.852 ± 0.004), and MDD (accuracy 0.753 ± 0.019, AUC 0.822 ± 0.010). Furthermore, PRSs from comorbid traits alone can effectively differentiate unaffected controls and patients with SCZ, BIP, and MDD (accuracy 0.861 ± 0.003, AUC 0.961 ± 0.041). Our results demonstrate that shared liabilities can be used effectively to improve the classification and differentiation of these disorders. The finding that PRSs from comorbid traits alone can classify and differentiate SCZ, BIP and MDD reasonably well implies that a majority of the risk variants composing target PRSs are shared with comorbid traits. Overall, our results suggest that a data-driven approach may be feasible to classify and differentiate these disorders

Rediscovering the value of families for psychiatric genetics research

As it is likely that both common and rare genetic variation are important for complex disease risk, studies that examine the full range of the allelic frequency distribution should be utilized to dissect the genetic influences on mental illness. The rate limiting factor for inferring an association between a variant and a phenotype is inevitably the total number of copies of the minor allele captured in the studied sample. For rare variation, with minor allele frequencies of 0.5% or less, very large samples of unrelated individuals are necessary to unambiguously associate a locus with an illness. Unfortunately, such large samples are often cost prohibitive. However, by using alternative analytic strategies and studying related individuals, particularly those from large multiplex families, it is possible to reduce the required sample size while maintaining statistical power. We contend that using whole genome sequence (WGS) in extended pedigrees provides a cost-effective strategy for psychiatric gene mapping that complements common variant approaches and WGS in unrelated individuals. This was our impetus for forming the “Pedigree-Based Whole Genome Sequencing of Affective and Psychotic Disorders” consortium. In this review, we provide a rationale for the use of WGS with pedigrees in modern psychiatric genetics research. We begin with a focused review of the current literature, followed by a short history of family-based research in psychiatry. Next, we describe several advantages of pedigrees for WGS research, including power estimates, methods for studying the environment, and endophenotypes. We conclude with a brief description of our consortium and its goals

Regional research priorities in brain and nervous system disorders

The characteristics of neurological, psychiatric, developmental and substance-use disorders in low-and middle-income countries are unique and the burden that they have will be different from country to country. Many of the differences are explained by the wide variation in population demographics and size, poverty, conflict, culture, land area and quality, and genetics. Neurological, psychiatric, developmental and substance-use disorders that result from, or are worsened by, a lack of adequate nutrition and infectious disease still afflict much of sub-Saharan Africa, although disorders related to increasing longevity, such as stroke, are on the rise. In the Middle East and North Africa, major depressive disorders and post-traumatic stress disorder are a primary concern because of the conflict-ridden environment. Consanguinity is a serious concern that leads to the high prevalence of recessive disorders in the Middle East and North Africa and possibly other regions. The burden of these disorders in Latin American and Asian countries largely surrounds stroke and vascular disease, dementia and lifestyle factors that are influenced by genetics. Although much knowledge has been gained over the past 10 years, the epidemiology of the conditions in low-and middle-income countries still needs more research. Prevention and treatments could be better informed with more longitudinal studies of risk factors. Challenges and opportunities for ameliorating nervous-system disorders can benefit from both local and regional research collaborations. The lack of resources and infrastructure for health-care and related research, both in terms of personnel and equipment, along with the stigma associated with the physical or behavioural manifestations of some disorders have hampered progress in understanding the disease burden and improving brain health. Individual countries, and regions within countries, have specific needs in terms of research priorities.Instituto de Investigaciones Bioquímicas de La Plat

Polygenic Risk Scores for Subtyping of Schizophrenia

Schizophrenia is a complex disorder with many comorbid conditions. In this study, we used polygenic risk scores (PRSs) from schizophrenia and comorbid traits to explore consistent cluster structure in schizophrenia patients. With 10 comorbid traits, we found a stable 4-cluster structure in two datasets (MGS and SSCCS). When the same traits and parameters were applied for the patients in a clinical trial of antipsychotics, the CATIE study, a 5-cluster structure was observed. One of the 4 clusters found in the MGS and SSCCS was further split into two clusters in CATIE, while the other 3 clusters remained unchanged. For the 5 CATIE clusters, we evaluated their association with the changes of clinical symptoms, neurocognitive functions, and laboratory tests between the enrollment baseline and the end of Phase I trial. Class I was found responsive to treatment, with significant reduction for the total, positive, and negative symptoms (p=0.0001, 0.0099, and 0.0028, respectively), and improvement for cognitive functions (VIGILANCE, p=0.0099; PROCESSING SPEED, p=0.0006; WORKING MEMORY, p=0.0023; and REASONING, p=0.0015). Class II had modest reduction of positive symptoms (p=0.0492) and better PROCESSING SPEED (p=0.0071). Class IV had a specific reduction of negative symptoms (p=0.0111) and modest cognitive improvement for all tested domains. Interestingly, Class IV was also associated with decreased lymphocyte counts and increased neutrophil counts, an indication of ongoing inflammation or immune dysfunction. In contrast, Classes III and V showed no symptom reduction but a higher level of phosphorus. Overall, our results suggest that PRSs from schizophrenia and comorbid traits can be utilized to classify patients into subtypes with distinctive clinical features. This genetic susceptibility based subtyping may be useful to facilitate more effective treatment and outcome prediction

Genetic and Morphological Features of Human iPSC-Derived Neurons with Chromosome 15q11.2 (BP1-BP2) Deletions

Producción CientíficaBackground: Copy number variation on chromosome 15q11.2 (BP1-BP2) causes deletion of CYFIP1, NIPA1, NIPA2 and TUBGCP5; it also affects brain structure and elevates risk for several neurodevelopmental disorders that are associated with dendritic spine abnormalities. In rodents, altered cyfip1 expression changes dendritic spine morphology, motivating analyses of human neuronal cells derived from iPSCs (iPSC-neurons). Methods: iPSCs were generated from a mother and her offspring, both carrying the 15q11.2 (BP1-BP2) deletion, and a non-deletion control. Gene expression in the deletion region was estimated using quantitative real-time PCR assays. Neural progenitor cells (NPCs) and iPSC-neurons were characterized using immunocytochemistry. Results: CYFIP1, NIPA1, NIPA2 and TUBGCP5 gene expression was lower in iPSCs, NPCs and iPSC-neurons from the mother and her offspring in relation to control cells. CYFIP1 and PSD95 protein levels were lower in iPSC-neurons derived from the CNV bearing individuals using Western blot analysis. At 10 weeks post-differentiation, iPSC-neurons appeared to show dendritic spines and qualitative analysis suggested that dendritic morphology was altered in 15q11.2 deletion subjects compared with control cells. Conclusions: The 15q11.2 (BP1-BP2) deletion is associated with reduced expression of four genes in iPSC-derived neuronal cells; it may also be associated altered iPSC-neuron dendritic morphology