scholarly journals Rare schizophrenia risk variant burden is conserved in diverse human populations

2022 ◽  
Author(s):  
Dongjing Liu ◽  
Dara Meyer ◽  
Brian Fennessy ◽  
Claudia Feng ◽  
Esther Cheng ◽  
...  
Keyword(s):  
Genetic Architecture ◽  
Large Scale ◽  
Current Knowledge ◽  
European Ancestry ◽  
P Value ◽  
Human Populations ◽  
Protein Coding ◽  
Coding Regions ◽  
Meta Analyses ◽  
Shared Risk

Schizophrenia is a chronic mental illness that is amongst the most debilitating conditions encountered in medical practice. A recent landmark schizophrenia study of the protein-coding regions of the genome identified a causal role for ten genes and a concentration of rare variant signals in evolutionarily constrained genes1. This study -- and most other large-scale human genetic studies -- was mainly composed of individuals of European ancestry, and the generalizability of the findings in non-European populations is unclear. To address this gap in knowledge, we designed a custom sequencing panel based on current knowledge of the genetic architecture of schizophrenia and applied it to a new cohort of 22,135 individuals of diverse ancestries. Replicating earlier work, cases carried a significantly higher burden of rare protein-truncating variants among constrained genes (OR=1.48, p-value = 5.4 x 10-6). In meta-analyses with existing schizophrenia datasets totaling up to 35,828 cases and 107,877 controls, this excess burden was largely consistent across five continental populations. Two genes (SRRM2 and AKAP11) were newly implicated as schizophrenia risk genes, and one gene (PCLO) was identified as a shared risk gene for schizophrenia and autism. Overall, our results lend robust support to the rare allelic spectrum of the genetic architecture of schizophrenia being conserved across diverse human populations.

scholarly journals A large Canadian cohort provides insights into the genetic architecture of human hair colour

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Frida Lona-Durazo ◽  
Marla Mendes ◽  
Rohit Thakur ◽  
Karen Funderburk ◽  
Tongwu Zhang ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Association Studies ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Hair Colour ◽  
Protein Coding ◽  
Coding Regions ◽  
Genome Wide ◽  
Causal Variants ◽  
Meta Analyses

AbstractHair colour is a polygenic phenotype that results from differences in the amount and ratio of melanins located in the hair bulb. Genome-wide association studies (GWAS) have identified many loci involved in the pigmentation pathway affecting hair colour. However, most of the associated loci overlap non-protein coding regions and many of the molecular mechanisms underlying pigmentation variation are still not understood. Here, we conduct GWAS meta-analyses of hair colour in a Canadian cohort of 12,741 individuals of European ancestry. By performing fine-mapping analyses we identify candidate causal variants in pigmentation loci associated with blonde, red and brown hair colour. Additionally, we observe colocalization of several GWAS hits with expression and methylation quantitative trait loci (QTLs) of cultured melanocytes. Finally, transcriptome-wide association studies (TWAS) further nominate the expression of EDNRB and CDK10 as significantly associated with hair colour. Our results provide insights on the mechanisms regulating pigmentation biology in humans.

scholarly journals The contribution of common regulatory and protein-coding TYR variants in the genetic architecture of albinism

2021 ◽  
Author(s):  
Vincent Michaud ◽  
Eulalie Lasseaux ◽  
David J Green ◽  
Dave T Gerrard ◽  
Claudio Plaisant ◽  
...  
Keyword(s):  
Genetic Architecture ◽  
Large Scale ◽  
Diagnostic Yield ◽  
Genetic Diseases ◽  
Gene Encoding ◽  
Protein Coding ◽  
Autosomal Recessive Disorders ◽  
Functional Variants ◽  
Prevalent Disease ◽  
Coding Variants

Genetic diseases have been historically segregated into rare Mendelian and common complex conditions. Large-scale studies using genome sequencing are eroding this distinction and are gradually unmasking the underlying complexity of human traits. We studied a cohort of 1,313 individuals with albinism aiming to gain insights into the genetic architecture of rare, autosomal recessive disorders. We investigated the contribution of regulatory and protein-coding variants at the common and rare ends of the allele-frequency spectrum. We focused on TYR, the gene encoding tyrosinase, and found that a promoter variant, TYR: c.-301C>T [rs4547091], modulates the penetrance of a prevalent, disease-associated missense change, TYR: c.1205G>A [rs1126809]. We also found that homozygosity for a haplotype formed by three common, functional variants, TYR: c.[-301C;575C>A;1205G>A], confers a high risk of albinism (OR>77) and is associated with reduced vision in UK Biobank participants. Finally, we report how the combined analysis of rare and common variants increases diagnostic yield and informs genetic counselling in families with albinism.

scholarly journals Transcriptomic and Epigenomic Landscape in Rett Syndrome

Biomolecules ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 967
Author(s):  
Domenico Marano ◽  
Salvatore Fioriniello ◽  
Maurizio D'Esposito ◽  
Floriana Della Ragione
Keyword(s):  
Rett Syndrome ◽  
Transcriptional Activation ◽  
Large Scale ◽  
Developmental Disorder ◽  
De Novo ◽  
Current Knowledge ◽  
Biological Processes ◽  
De Novo Mutations ◽  
Protein Coding ◽  
Methylated Dna

Rett syndrome (RTT) is an extremely invalidating, cureless, developmental disorder, and it is considered one of the leading causes of intellectual disability in female individuals. The vast majority of RTT cases are caused by de novo mutations in the X-linked Methyl-CpG binding protein 2 (MECP2) gene, which encodes a multifunctional reader of methylated DNA. MeCP2 is a master epigenetic modulator of gene expression, with a role in the organization of global chromatin architecture. Based on its interaction with multiple molecular partners and the diverse epigenetic scenario, MeCP2 triggers several downstream mechanisms, also influencing the epigenetic context, and thus leading to transcriptional activation or repression. In this frame, it is conceivable that defects in such a multifaceted factor as MeCP2 lead to large-scale alterations of the epigenome, ranging from an unbalanced deposition of epigenetic modifications to a transcriptional alteration of both protein-coding and non-coding genes, with critical consequences on multiple downstream biological processes. In this review, we provide an overview of the current knowledge concerning the transcriptomic and epigenomic alterations found in RTT patients and animal models.

scholarly journals Exome wide association study on Albuminuria identifies a novel rare variant inCUBNand additional genes, in 33985 Europeans with and without diabetes

2018 ◽  
Author(s):  
Tarunveer S. Ahluwalia ◽  
Christina-Alexendra Schulz ◽  
Johannes Waage ◽  
Tea Skaaby ◽  
Niina Sandholm ◽  
...  
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Association Study ◽  
Genetic Architecture ◽  
European Ancestry ◽  
Common Variants ◽  
Multiple Testing Correction ◽  
Meta Analyses ◽  
Coding Variants ◽  
Prevention Of Diabetes

AbstractIdentifying rare coding variants associated with albuminuria may open new avenues for preventing chronic kidney disease (CKD) and end-stage renal disease which are highly prevalent in patients with diabetes. Efforts to identify genetic susceptibility variants for albuminuria have so far been limited with the majority of studies focusing on common variants.We performed an exome-wide association study to identify coding variants in a two phase (discovery and replication) approach, totaling to 33,985 individuals of European ancestry (15,872 with and 18,113 without diabetes) and further testing in Greenlanders (n = 2,605). We identify a rare (MAF: 0.8%) missense (A1690V) variant inCUBN(rs141640975, β=0.27, p=1.3 × 10−11) associated with albuminuria as a continuous measure in the combined European meta-analyses. Presence of each rare allele of the variant was associated with a 6.4% increase in albuminuria. The rareCUBNvariant had 3 times stronger effect in individuals with diabetes compared to those without(pinteraction:5.4 × 10−4, βDM: 0.69, βnonDM:0.20) in the discovery meta-analyses. Geneaggregate tests based on rare and common variants identify three additional genes associated with albuminuria(HES1, CDC73, andGRM5)after multiple testing correction (P_bonferroni<2.7 × 10−6).The current study identifies a rare coding variant in theCUBNlocus and other potential genes associated with albuminuria in individuals with and without diabetes. These genes have been implicated in renal and cardiovascular dysfunction. These findings provide new insights into the genetic architecture of albuminuria and highlight novel target genes and pathways for prevention of diabetes-related kidney disease.Significance statementIncreased albuminuria is a key manifestation of major health burdens, including chronic kidney disease and/or cardiovascular disease. Although being partially heritable, there is a lack of knowledge on rare genetic variants that contribute to albuminuria. The current study describes the discovery and validation, of a new rare gene mutation (~1%) in theCUBNgene which associates with increased albuminuria. Its effect multiplies 3 folds among diabetes cases compared to non diabetic individuals. The study further uncovers 3 additional genes modulating albuminuria levels in humans. Thus the current study findings provide new insights into the genetic architecture of albuminuria and highlight novel genes/pathways for prevention of diabetes related kidney disease.

scholarly journals The genetic architecture of sporadic and recurrent miscarriage

2019 ◽  
Author(s):  
Triin Laisk ◽  
Ana Luiza G Soares ◽  
Teresa Ferreira ◽  
Jodie N Painter ◽  
Samantha Laber ◽  
...  
Keyword(s):  
Genetic Architecture ◽  
Large Scale ◽  
Recurrent Miscarriage ◽  
Meta Analysis ◽  
Chromosome 9 ◽  
Extravillous Trophoblast ◽  
European Ancestry ◽  
Association Analyses ◽  
Progesterone Production ◽  
Genome Wide

Miscarriage is a common complex trait that affects 10-25% of clinically confirmed pregnancies1,2. Here we present the first large-scale genetic association analyses with 69,118 cases from five different ancestries for sporadic miscarriage and 750 cases of European ancestry for recurrent miscarriage, and up to 359,469 female controls. We identify one genome-wide significant association on chromosome 13 (rs146350366, minor allele frequency (MAF) 1.2%,Pmeta=3.2×-8(CI) 1.2-1.6) for sporadic miscarriage in our European ancestry meta-analysis (50,060 cases and 174,109 controls), located nearFGF9involved in pregnancy maintenance3and progesterone production4. Additionally, we identified three genome-wide significant associations for recurrent miscarriage, including a signal on chromosome 9 (rs7859844, MAF=6.4%,Pmeta=1.3×-8in controlling extravillous trophoblast motility5. We further investigate the genetic architecture of miscarriage with biobank-scale Mendelian randomization, heritability and, genetic correlation analyses. Our results implicate that miscarriage etiopathogenesis is partly driven by genetic variation related to gonadotropin regulation, placental biology and progesterone production.

scholarly journals Analysis of Polygenic Score Usage and Performance in Diverse Human Populations

2018 ◽  
Author(s):  
LE Duncan ◽  
H Shen ◽  
B Gelaye ◽  
KJ Ressler ◽  
MW Feldman ◽  
...  
Keyword(s):  
Large Scale ◽  
Association Studies ◽  
African Ancestry ◽  
Population Level ◽  
European Ancestry ◽  
Human Populations ◽  
Genome Wide Association Studies ◽  
Polygenic Score ◽  
Methodological Choices ◽  
Polygenic Scores

AbstractStudies examining relationships between genotypic and phenotypic variation have historically been carried out on people of European ancestry. Efforts are underway to address this limitation, but until they succeed, the legacy of a Euro-centric bias will continue to hinder research, including the use of polygenic scores, which are individual-level metrics of genetic risk. Ongoing debate surrounds the generalizability of polygenic scores based on genome-wide association studies (GWAS) conducted in European ancestry samples, to non-European ancestry samples. We analyzed the first decade of polygenic scoring studies (2008-2017, inclusive), and found that 67% of studies included exclusively European ancestry participants and another 19% included only East Asian ancestry participants. Only 3.8% of studies were carried out on samples of African, Hispanic, or Indigenous peoples. We find that effect sizes for European ancestry-derived polygenic scores are only 36% as large in African ancestry samples, as in European ancestry samples (t=−10.056, df=22, p=5.5×10−10). Analyzing global populations, we show that relationships between height polygenic scores and height are highly dependent on methodological choices in polygenic score construction, highlighting the need for caution in interpreting population level differences in distributions of polygenic scores, as currently calculated. These findings bolster the rationale for large-scale GWAS in diverse human populations and highlight the need for better handling of linkage disequilibrium and variant frequencies when applying scores to non-European samples.

Abstract 048: Association Analyses of up to ∼263,000 Individuals Provide New Insights into the Biology and Genetic Architecture of the Extremes of Anthropometric Traits

Circulation ◽  
2012 ◽  
Vol 125 (suppl_10) ◽  
Author(s):  
Erik Ingelsson ◽  
Reedik Mägi ◽  
Stefan Gustafsson ◽  
Andrea Ganna ◽  
Eleanor Wheeler ◽  
...  
Keyword(s):  
General Population ◽  
Genetic Architecture ◽  
Class Ii ◽  
Overweight And Obesity ◽  
European Ancestry ◽  
Continuous Measure ◽  
Phenotypic Variance ◽  
Obesity Class ◽  
Genome Wide ◽  
Meta Analyses

Anthropometric traits have a strong genetic component with heritability estimates between 40–70% for body mass index (BMI) and ∼80% for height; however, established loci only account for a small fraction (1–10%) of the phenotypic variance of these complex traits. It has been hypothesized that the extremes of the distributions of these traits are enriched for genetic loci and may have a distinct genetic architecture compared to the general population. To explore the genetic contribution of the extremes (defined as the upper and lower 5th percentile) of BMI, height, and waist-hip ratio [WHR] adjusted for BMI and clinical classes of obesity (including overweight and obesity classes I, II, and III), we conducted meta-analyses of ∼2.8 million SNPs from 49 genome-wide association studies of European ancestry totaling from 4,774 cases and 5,481 controls (extreme WHR) to 93,015 cases and 65,840 controls (overweight) for these traits. The most promising loci from each meta-analysis (P<5 x 10 −6 ) were taken forward for replication into up to 65,332 cases and 39,294 controls. In meta-analyses of the combined stages, we observed genome-wide significant associations (P<5 x 10 −8 ) for 191 loci (extreme BMI, height and WHR: 10, 96 and 2 loci, respectively; overweight and obesity classes I, II, and III: 25, 33, 24 and 1 loci, respectively). Out of these 191 loci, we identified 9 novel loci that have not been previously associated with anthropometric traits when studying the whole distributions (P<5 x 10 −8 ), including three loci for extreme height ( ZNF36, H6PD , RSRC1 ), three for obesity class II ( OLFM4 , HS6ST3 , AK5/ZZZ3 ), two for obesity class I ( GNAI3/MIR197/GNAT2, HNF4G ), and two for overweight ( RPTOR, HNF4G ). Several loci for obesity were located near genes expressed primarily in the brain (e.g. CACNA1D, AK5 ), suggesting a neuronal influence, whereas the loci for overweight were near genes involved in other processes, such as mTOR signaling (e.g. RPTOR ). All of the novel loci discovered for the extremes and obesity classes were nominally associated with the trait as a continuous measure in the general population (N = 123,865) but at a lesser significance level (P range: 0.003 – 1.4x10 −5 ). A polygenetic risk score including all independent SNPs associated with BMI (at different P-value thresholds) revealed that significantly more of the variance was explained for the extremes of BMI and obesity class II, than for BMI as a continuous measure in the population (variance explained, 20%, 10% and 5%, respectively), suggesting a greater genetic influence on the extremes. Investigations are underway to evaluate haplotypes and additional signals at known BMI and height loci in the extreme samples to explore allelic heterogeneity. In conclusion, this study identifies additional loci and provides novel insights into the genetic architecture of the extremes of anthropometric traits.

scholarly journals Quantifying unobserved protein-coding variants in human populations provides a roadmap for large-scale sequencing projects

2016 ◽  
Vol 7 (1) ◽  
Author(s):  
James Zou ◽  
Gregory Valiant ◽  
Paul Valiant ◽  
Konrad Karczewski ◽  
Siu On Chan ◽  
...  
Keyword(s):  
Large Scale ◽  
Human Populations ◽  
Protein Coding ◽  
Coding Variants

scholarly journals Quantifying the unobserved protein-coding variants in human populations provides a roadmap for large-scale sequencing projects

2015 ◽  
Author(s):  
James Zou ◽  
Gregory Valiant ◽  
Paul Valiant ◽  
Konrad Karczewski ◽  
Siu On Chan ◽  
...  
Keyword(s):  
Frequency Distribution ◽  
Statistical Power ◽  
Large Scale ◽  
Rare Variants ◽  
Human Populations ◽  
Loss Of Function ◽  
Protein Coding ◽  
Missense Variants ◽  
Healthy Humans ◽  
Coding Variants

As new proposals aim to sequence ever larger collection of humans, it is critical to have a quantitative framework to evaluate the statistical power of these projects. We developed a new algorithm, UnseenEst, and applied it to the exomes of 60,706 individuals to estimate the frequency distribution of all protein-coding variants, including rare variants that have not been observed yet in the current cohorts. Our results quantified the number of new variants that we expect to identify as sequencing cohorts reach hundreds of thousands of individuals. With 500K individuals, we find that we expect to capture 7.5% of all possible loss-of-function variants and 12% of all possible missense variants. We also estimate that 2,900 genes have loss-of-function frequency of less than 0.00001 in healthy humans, consistent with very strong intolerance to gene inactivation.

scholarly journals Large-scale inference of competing endogenous RNA networks with sparse partial correlation

2019 ◽  
Vol 35 (14) ◽  
pp. i596-i604 ◽  
Author(s):  
Markus List ◽  
Azim Dehghani Amirabad ◽  
Dennis Kostka ◽  
Marcel H Schulz
Keyword(s):  
Large Scale ◽  
The Cancer Genome Atlas ◽  
Supplementary Information ◽  
P Value ◽  
Protein Coding ◽  
Individual Mirnas ◽  
Competing Endogenous Rnas ◽  
Cancer Genome Atlas ◽  
Gene Regulatory ◽  
Novel Protein

AbstractMotivationMicroRNAs (miRNAs) are important non-coding post-transcriptional regulators that are involved in many biological processes and human diseases. Individual miRNAs may regulate hundreds of genes, giving rise to a complex gene regulatory network in which transcripts carrying miRNA binding sites act as competing endogenous RNAs (ceRNAs). Several methods for the analysis of ceRNA interactions exist, but these do often not adjust for statistical confounders or address the problem that more than one miRNA interacts with a target transcript.ResultsWe present SPONGE, a method for the fast construction of ceRNA networks. SPONGE uses ’multiple sensitivity correlation’, a newly defined measure for which we can estimate a distribution under a null hypothesis. SPONGE can accurately quantify the contribution of multiple miRNAs to a ceRNA interaction with a probabilistic model that addresses previously neglected confounding factors and allows fast P-value calculation, thus outperforming existing approaches. We applied SPONGE to paired miRNA and gene expression data from The Cancer Genome Atlas for studying global effects of miRNA-mediated cross-talk. Our results highlight already established and novel protein-coding and non-coding ceRNAs which could serve as biomarkers in cancer.Availability and implementationSPONGE is available as an R/Bioconductor package (doi: 10.18129/B9.bioc.SPONGE).Supplementary informationSupplementary data are available at Bioinformatics online.

Sign in / Sign up

Export Citation Format

Share Document