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At least 127 records · Page 7Linked to original sources
PubMed2003

A full-likelihood method for the evaluation of causality of sequence variants from family data.

In many disease genes, a substantial fraction of all rare variants detected cannot yet be used for genetic counselling because of uncertainty about their association with disease. One approach to the characterization of these unclassified variants is the analysis of patterns of cosegregation with disease in affected carrier families. Petersen et al. previously provided a simplistic Bayesian method for evaluation of causality of such sequence variants. In the present report, we propose a more general method based on the full pedigree likelihood, and we show that the use of this method can provide more accurate and informative assessment of causality than could the previous method. We further show that it is important that the pedigree information be as complete as possible and that the distinction be made between unaffected individuals and those of unknown phenotype.

Causality↗
PubMed2025

Prioritization of causal genes from genome-wide association studies by Bayesian data integration across loci.

MOTIVATION: Genome-wide association studies (GWAS) have identified genetic variants, usually single-nucleotide polymorphisms (SNPs), associated with human traits, including disease and disease risk. These variants (or causal variants in linkage disequilibrium with them) usually affect the regulation or function of a nearby gene. A GWAS locus can span many genes, however, and prioritizing which gene or genes in a locus are most likely to be causal remains a challenge. Better prioritization and prediction of causal genes could reveal disease mechanisms and suggest interventions. RESULTS: We describe a new Bayesian method, termed SigNet for significance networks, that combines information both within and across loci to identify the most likely causal gene at each locus. The SigNet method builds on existing methods that focus on individual loci with evidence from gene distance and expression quantitative trait loci (eQTL) by sharing information across loci using protein-protein and gene regulatory interaction network data. In an application to cardiac electrophysiology with 226 GWAS loci, only 46 (20%) have within-locus evidence from Mendelian genes, protein-coding changes, or colocalization with eQTL signals. At the remaining 180 loci lacking functional information, SigNet selects 56 genes other than the minimum distance gene, equal to 31% of the information-poor loci and 25% of the GWAS loci overall. Assessment by pathway enrichment demonstrates improved performance by SigNet. Review of individual loci shows literature evidence for genes selected by SigNet, including PMP22 as a novel causal gene candidate.

Genome-Wide Association Study↗
PubMed2026

Mapping the causal chain from genetic risk variants to lipid dysmetabolism in Parkinson's disease.

The molecular pathways linking genetic variants to Parkinson's disease (PD) onset and progression remain incompletely defined; however, risk alleles in multiple genes, including GBA1, strongly implicate lipid metabolism. To systematically identify causal biomarker signatures, we analysed comprehensive metabolome profiles from blood plasma in 149 PD patients and 150 controls, along with complementary genetic, RNA-sequencing and metabolic data from other available clinical and pathologic cohorts. Using colocalization and summary-data-based Mendelian randomization, we tested whether expression and metabolic quantitative trait loci mediate the association between implicated genetic variants and PD risk. We further integrated differential metabolomics and proteomics from blood and brain to reveal pertinent mechanisms. We show that common PD risk variants at the serine palmitoyltransferase small subunit B (SPTSSB) locus, a key regulator of de novo sphingolipid biosynthesis, are associated with increased SPTSSB brain expression and elevated plasma ceramides. Additional analyses strongly support our hypothesis that a common SPTSSB causal variant is responsible for PD risk as well as the expression and metabolic quantitative trait loci. Multiple sphingolipids and fatty acid derivatives were perturbed in PD, and we identified both unique and shared features with the Alzheimer's disease metabolome. A PD acylcarnitine signature was further replicated in human post-mortem brain tissue, when comparing those with or without preclinical Lewy body pathology. Integrated analysis of complementary brain proteomic profiles revealed dysregulation of mitochondrial processes dependent on acylcarnitines, including fatty acid beta-oxidation, the tricarboxylic acid cycle and oxidative phosphorylation. Our results identify promising biomarkers and reveal a causal chain linking genetic variation to altered gene/protein expression, lipid dysmetabolism, and the manifestation of PD.

Humans↗
PubMed2026

A phenotypic paradigm for cerebral palsy genetics.

Cerebral palsy (CP) represents a clinically and etiologically heterogeneous group of permanent but not unchanging disorders of movement, posture, and motor function resulting from non-progressive disturbances of the developing fetal or infant brain. Pathogenic variants in Mendelian disease-associated genes can be found in a subset of individuals with CP, with variants deemed causal of CP having been published for at least 515 genes. Currently, controversy exists as to whether to interpret such pathogenic variants as causing CP, whether the diagnosis instead should be "CP mimic," or whether a clinical diagnosis of CP should coexist with the molecular diagnosis of a Mendelian disease. Accordingly, there is no universally accepted model of the genetic architecture of CP. Here, we present a statistical approach that treats CP as a phenotypic feature for which some genetic disorders confer an increased risk. Based on comprehensive literature curation, we show that the null hypothesis of no CP association can be rejected for only 89 of the 515 genes. We applied these findings to the analysis of a cohort of 460 children diagnosed with CP in the Shriner Children's network who underwent genome sequencing. We identified pathogenic or likely pathogenic (P/LP) variants in 60 genes in 15.8% of the children. Only 16 of the 60 genes had significant evidence for CP association in our literature analysis. Our results suggest that a stratified approach to attributing causality to genetic variants in CP could support precision genomic medicine for affected individuals.

Humans↗
PubMed2025

FINEMAP-miss: fine-mapping genome-wide association studies with missing genotype information.

MOTIVATION: The most informative genome-wide association studies (GWAS) are meta-analyses that have combined multiple studies to increase the GWAS sample size. Statistical fine-mapping is a key downstream analysis of GWAS to jointly evaluate the probability of causality of all variants in a genomic region of interest. Current fine-mapping methods are miscalibrated in the meta-analysis setting due to variation in sample size across the variants. RESULTS: We introduce FINEMAP-miss, a new fine-mapping method that extends the FINEMAP model to account for variant-specific missingness. We show that FINEMAP-miss is well-calibrated in meta-analysis simulations where the standard fine-mapping fails. Compared to the summary statistics imputation approach, FINEMAP-miss provides clear improvement when the causal variants have low imputation information or when the sample size or complexity of the meta-analysis setting increase. We successfully apply FINEMAP-miss on a breast cancer GWAS meta-analysis where neither the standard fine-mapping nor the summary statistics imputation are applicable. AVAILABILITY: An open source implementation of FINEMAP-miss as an R package ("finemapmiss") is available at https://github.com/JoonasKartau/finemapmiss. The archived version of FINEMAP-miss used for this publication can be found on Zenodo at https://doi.org/10.5281/zenodo.17492622. SUPPLEMENTARY INFORMATION: is available at the journal's web site.

Genome-Wide Association Study↗
PubMed2006

Time-variant analysis of fast-fMRI and dynamic contrast agent MRI sequences as examples of 4-dimensional image analysis.

OBJECTIVES: Image sequences with time-varying information content need appropriate analysis strategies. The exploration of directed information transfer (interactions) between neuronal assemblies is one of the most important aims of current functional MRI (fMRI) analysis. Additionally, we examined perfusion maps in dynamic contrast agent MRI sequences of stroke patients. In this investigation, the focus centers on distinguishing between brain areas with normal and reduced perfusion on the basis of the dynamics of contrast agent inflow and washout. METHODS: Fast fMRI sequences were analyzed with time-variant Granger causality (tvGC). The tvGC is based on a time-variant autoregressive model and is used for the quantification of the directed information transfer between activated brain areas. Generalized Dynamic Neural Networks (GDNN) with time-variant weights were applied on dynamic contrast agent MRI sequences as a nonlinear operator in order to enhance differences in the signal courses of pixels of normal and injured tissues. RESULTS: A simple motor task (self-paced finger tapping) is used in an fMRI design to investigate directed interactions between defined brain areas. A significant information transfer can be determined for the direction primary motor cortex to supplementary motor area during a short time period of about five seconds after stimulus. The analysis of dynamic contrast agent MRI sequences demonstrates that the trained GDNN enables a reliable tissue classification. Three classes are of interest: normal tissue, tissue at risk for death, and dead tissue. CONCLUSIONS: The time-variant multivariate analysis of directed information transfer derived from fMRI sequences and the computation of perfusion maps by GDNN demonstrate that dynamic analysis methods are essential tools for 4D image analysis.

Cerebrovascular Circulation↗
PubMed2002

[Brief causal relations in EEG based on adaptive Granger causality].

Commonly, coherence and correlation are used to describe interrelations between EEG signals. But, on this basis, the investigation of causality or direction of interrelations is not possible. The general idea of causality between two signals may be expressed in terms of upgrading the predictability of one signal bye the knowledge of the past of the other signal. The best established approach in this context is the so-called Granger causality. The study present an adaptive estimation of Granger causality, which allows to detect dynamic causal relations within time intervals of less 100 ms. The time-variant Granger causality is applied to EEG data of the Stroop task. It could be shown, that conflict situation generates a dense web of directed interactions from posterior to anterior cortical areas.

Adult↗
PubMed2026

Non-coding regulatory variants in adolescent idiopathic scoliosis risk and pathogenesis.

Adolescent idiopathic scoliosis is a common pediatric musculoskeletal disease that has significant impacts on childhood quality of life. Recent genome-wide association studies have identified dozens of genetic risk loci and hundreds of risk variants that primarily reside in non-coding regions of the genome. Follow up studies suggest a complex genetic architecture in which several tissues may be affected, however few causal disease variants have been identified. Here we review the functional AIS-associated variants that have been identified, how they may contribute to disease etiology, and necessary advancements that will link the effects of non-coding variants to disease mechanisms.

Humans↗
PubMed2006

Virtues and woes of AChE alternative splicing in stress-related neuropathologies.

The ACh hydrolyzing enzyme acetylcholinesterase (AChE) is a combinatorial series of proteins with variant N and C termini generated from alternate promoter usage and 3' alternative splicing. Neuronal AChE variants show indistinguishable enzymatic activity yet differ in their expression, multimeric assembly and membrane-association patterns. Differentially induced under stress, they show distinct non-hydrolytic properties and interact with different protein partners. Recent findings suggest that transcriptional and post-transcriptional regulation of AChE pre-mRNA is a neuroprotection strategy but might involve long-term damage. Specifically, variant-specific causal involvement of AChE in the progression of both neurodegenerative diseases (e.g. Alzheimer's and Parkinson's diseases) and neuromuscular syndromes (e.g. myasthenia gravis) raises the possibility that future therapeutic drugs might target specific AChE variant(s) or the corresponding RNA transcripts.

Acetylcholinesterase↗
PubMed2002

The genetic basis of dyslexia.

Dyslexia, a disorder of reading and spelling, is a heterogeneous neurological syndrome with a complex genetic and environmental aetiology. People with dyslexia differ in their individual profiles across a range of cognitive, physiological, and behavioural measures related to reading disability. Some or all of the subtypes of dyslexia might have partly or wholly distinct genetic causes. An understanding of the role of genetics in dyslexia could help to diagnose and treat susceptible children more effectively and rapidly than is currently possible and in ways that account for their individual disabilities. This knowledge will also give new insights into the neurobiology of reading and language cognition. Genetic linkage analysis has identified regions of the genome that might harbour inherited variants that cause reading disability. In particular, loci on chromosomes 6 and 18 have shown strong and replicable effects on reading abilities. These genomic regions contain tens or hundreds of candidate genes, and studies aimed at the identification of the specific causal genetic variants are underway.

Animals↗
PubMed2002

Evaluation of the positional candidate gene CHRNA7 at the juvenile myoclonic epilepsy locus (EJM2) on chromosome 15q13-14.

A previous study of 34 nuclear pedigrees segregating juvenile myoclonic epilepsy (JME) gave significant evidence of linkage with heterogeneity to marker loci on chromosome 15q13-14 close to the candidate gene CHRNA7 (Hum. Mol. Genet. 6 (1997) 1329). The aim of this work was to further evaluate the putative aetiological role of CHRNA7 in JME within the 34 families originally described, and to assess the contribution of this locus to a broader phenotype of idiopathic generalised epilepsy (IGE). Multipoint linkage analysis and intrafamilial association studies were performed with microsatellite markers that encompass both CHRNA7 and its partial duplication (CHRFAM7A). A maximum HLOD of 3.45 [alpha=0.58; (Zall=2.88, P=0.0008)] was observed 8 cM distal to D15S1360, a CHRNA7 intragenic marker. Significant exclusion lod scores were obtained across the region in 12 mixed phenotype JME/IGE families. Mutation screening of the CHRNA7 gene (and consequently exons 5-10 of CHRFAM7A) and its putative promoter sequence identified a total of 13 sequence variants across 23 of 34 JME-affected families. Two variants (c.1354G>A and c.1466C>T) are predicted to result in amino acid changes and one (IVS9+5G>A) is predicted to result in aberrant transcript splicing. However, none of the variants alone appeared either necessary or sufficient to cause JME in the families in which they occurred. In conclusion, linkage analyses continue to support the existence of a locus on chromosome 15q13-14 that confers susceptibility to JME but not to a broader IGE phenotype. Causal sequence variants in the positional candidate CHRNA7 have not been identified but the presence of multiple segmental duplications in this region raises the possibility of undetected disease-causing genomic rearrangements.

Chromosome Mapping↗
PubMed2006

Identification of three novel mutations in the GATA3 gene responsible for familial hypoparathyroidism and deafness in the Chinese population.

BACKGROUND: Familial hypoparathyroidism may be caused by mutations of several genes. The CaSR and GATA3 genes are the two candidates most commonly responsible for this condition. OBJECTIVES: We collected five unrelated families with familial hypoparathyroidism and examined their CaSR and GATA3 genes. METHODS: Blood samples from these five families and 50 ethnically matched unrelated controls were acquired. Biochemistry screening and formal audiogram were performed to evaluate the affected individuals. All the exons and exon-intron boundaries of the GATA3 and CaSR genes were sequenced. RESULTS: We identified three novel mutations in the GATA3 gene responsible for familial hypoparathyroidism and deafness: 1) a frameshift deletion occurring in codon 160 (478delG) was hypothesized to disrupt dual zinc fingers as well as one transactivating domain; 2) a donor splice site mutation at exon 4/intron 4 boundary (IVS4 + 2 T to GCTTACTTCCC) was predicted to lead to truncated GATA3 proteins that lack both N- and C-terminal zinc-containing fingers; and 3) a missense mutation R353S was predicted to disrupt the helical turn and thus changed the angle between the C-terminal zinc finger and the adjacent C-terminal tail. Except for a previously described polymorphism, G990R, we did not find any genetic variants in the CaSR gene. CONCLUSIONS: This is the first article presenting mutations of the GATA3 gene responsible for familial hypoparathyroidism and deafness in the Chinese population. Our results expand the spectrum of mutations and report the first splice donor site mutation of the GATA3 gene. In contrast, we do not find causal sequence variants of the CaSR gene from our collection of familial hypoparathyroidism.

Adolescent↗
PubMed2025

Identifying independent causal cell types for human diseases and risk variants.

The SNP-heritability of human diseases is extremely enriched in candidate regulatory elements (cREs) from disease-relevant cell types. Critical next steps are to understand whether these enrichments are driven by multiple causal cell types and whether individual variants impact disease risk via a single or multiple of cell types. Here, we propose CT-FM and CT-FM-SNP, 2 methods accounting for cREs shared across cell types to identify independent sets of causal cell types for a trait and its candidate causal variants, respectively. We applied CT-FM to 63 GWAS summary statistics (average N = 417K) using 924 cRE annotations, primarily from ENCODE4. CT-FM inferred 79 sets of causal cell types, with corresponding SNP-annotations explaining 39.0 ± 1.8% of trait SNP-heritability. It identified 14 traits with independent causal cell types, uncovering previously unexplored cellular mechanisms in height, schizophrenia and autoimmune diseases. We applied CT-FM-SNP to 39 UK Biobank traits and predicted high-confidence causal cell types for 3,091 candidate causal non-coding SNPs-trait pairs. Our results suggest that most SNPs affect a phenotype via a single set of cell types, whereas pleiotropic SNPs might target different cell types depending on the phenotype context. Altogether, CT-FM and CT-FM-SNP shed light on how genetic variants act collectively and individually at the cellular level to affect disease risk.

Journal Article↗
PubMed2025

Multi-omic phenotyping of iPSC-derived neurons harboring the MAPT V337M mutation reveals tau hypophosphorylation and perturbed axon morphology pathways.

Tau aggregation is a hallmark of several neurodegenerative diseases, including Alzheimer's disease and frontotemporal dementia. There are disease-causing variants of the tau-encoding gene, MAPT, and the presence of tau aggregates is highly correlated with disease progression. However, the molecular mechanisms linking pathological tau to neuronal dysfunction are not well understood. This is in part due to an incomplete understanding of the normal functions of tau in development and aging, and how the associated molecular and cellular processes change in the context of causal disease variants of tau. To address these questions in an unbiased manner, we conducted multi-omic characterization of iPSC-derived neurons harboring the MAPT V337M mutation or MAPT knockdown. RNA-seq and phosphoproteomics revealed that both V337M mutation and tau knockdown perturbed levels of transcripts and phosphorylation of proteins related to axonogenesis or axon morphology. Surprisingly, we found that neurons with V337M tau had much lower tau phosphorylation than neurons with WT tau. Functional genomics screens uncovered regulators of tau phosphorylation in neurons and found that factors involved in axonogenesis modified tau phosphorylation in both MAPT WT and MAPT V337M neurons. Intriguingly, the p38 MAPK pathway specifically modified tau phosphorylation in MAPT V337M neurons. We propose that V337M tau perturbs tau phosphorylation and axon morphology pathways that are relevant to the normal function of tau, which could contribute to previously reported cognitive changes in preclinical MAPT variant carriers.

Journal Article↗
PubMed2003

Emerging trends in the search for genetic variants predisposing to human obesity.

PURPOSE OF REVIEW: The models currently proposed for the genetic architecture of obesity are critically reviewed in the light of recent developments in the search for genetic causes of this condition. RECENT FINDINGS: As for many other 'complex' diseases, most of the genetic variants predisposing to human obesity have not yet been identified. To date, investigation of the genetic contribution to obesity has been conducted according to two main hypotheses. The common disease/common variant hypothesis proposes that the genetic architecture of complex diseases (including obesity) is likely to consist of a limited number of alleles, each conferring a small increase in risk to the individual. Alternatively, it has also been proposed that complex diseases such as obesity may instead result from the effects of a large number of rare variants, with substantial allelic heterogeneity at disease-causing loci. These two hypotheses have shaped strategies for the identification of disease genes, including the use of linkage analysis, association studies and the systematic sequencing of candidate genes. Linkage studies have recently been very successful in identifying new genes in which mutations cause rare monogenic syndromes of obesity. In common obesity, numerous linkage and association studies have suggested that an increasing number of genetic loci could be involved. Overall, however, these studies have failed to identify the causal genetic variants. In contrast, the direct sequencing of well-chosen candidate genes has led to the identification of numerous rare alleles causing both syndromic and common obesity, which are less severe forms of the condition in humans. SUMMARY: The genetic architecture of obesity is still a matter of debate. The previously accepted hypothesis of a small number of common variants has been undermined by the low reproducibility of association studies and inconsistencies among genome scans for obesity. While high-throughput association mapping of candidate regions holds some promise for the identification of common susceptibility alleles, it must also be considered that the genetic predisposition to obesity may instead result from multiple rare variants in a large number of genes.

Alleles↗
PubMed2001

Genetic variation in the 5q31 cytokine gene cluster confers susceptibility to Crohn disease.

Linkage disequilibrium (LD) mapping provides a powerful method for fine-structure localization of rare disease genes, but has not yet been widely applied to common disease. We sought to design a systematic approach for LD mapping and apply it to the localization of a gene (IBD5) conferring susceptibility to Crohn disease. The key issues are: (i) to detect a significant LD signal (ii) to rigorously bound the critical region and (iii) to identify the causal genetic variant within this region. We previously mapped the IBD5 locus to a large region spanning 18 cM of chromosome 5q31 (P<10(-4)). Using dense genetic maps of microsatellite markers and single-nucleotide polymorphisms (SNPs) across the entire region, we found strong evidence of LD. We bound the region to a common haplotype spanning 250 kb that shows strong association with the disease (P< 2 x 10(-7)) and contains the cytokine gene cluster. This finding provides overwhelming evidence that a specific common haplotype of the cytokine region in 5q31 confers susceptibility to Crohn disease. However, genetic evidence alone is not sufficient to identify the causal mutation within this region, as strong LD across the region results in multiple SNPs having equivalent genetic evidence-each consistent with the expected properties of the IBD5 locus. These results have important implications for Crohn disease in particular and LD mapping in general.

Chromosome Mapping↗
PubMed2006

In vivo RNA interference demonstrates a role for Nramp1 in modifying susceptibility to type 1 diabetes.

Type 1 diabetes is an autoimmune disease influenced by multiple genetic loci. Although more than 20 insulin-dependent diabetes (Idd) loci have been implicated in the nonobese diabetic (NOD) mouse model, few causal gene variants have been identified. Here we show that RNA interference (RNAi) can be used to probe candidate genes in this disease model. Slc11a1 encodes a phagosomal ion transporter, Nramp1, that affects resistance to intracellular pathogens and influences antigen presentation. This gene is the strongest candidate among the 42 genes in the Idd5.2 region; a naturally occurring mutation in the protective Idd5.2 haplotype results in loss of function of the Nramp1 protein. Using lentiviral transgenesis, we generated NOD mice in which Slc11a1 is silenced by RNAi. Silencing reduced the frequency of type 1 diabetes, mimicking the protective Idd5.2 region. Our results demonstrate a role for Slc11a1 in modifying susceptibility to type 1 diabetes and illustrate that RNAi can be used to study causal genes in a mammalian model organism.

Animals↗
PubMed2026

A single-cell study of transcription and RNA splicing in MDD and ALC.

Major depressive disorder (MDD) and problematic alcohol use (ALC) commonly co-occur, yet the extent, genomic distribution, and biological context of their shared genetic architecture remain incompletely understood. Here, we integrated genome-wide and local genetic architecture analyses with tissue, spatial, single-cell, and multi-omics analyses to characterize the shared genetic basis of MDD and ALC. Across methods, the two phenotypes showed a consistent positive genetic correlation (rg = 0.380-0.582). MiXeR estimated that they shared approximately 5479 variants with non-zero additive genetic effects, with the shared component accounting for a larger proportion of the polygenic architecture of ALC than of MDD. Local analyses further indicated that shared genetic covariance was concentrated in a limited number of genomic segments. At the tissue and cellular levels, genetic signals were primarily associated with central nervous system tissues and neuronal lineages, with additional support for oligodendrocyte-related populations; the two phenotypes also differed in the distribution and within-cell-type heterogeneity of disease-relevance scores. Multi-omics integration prioritized MED19 and ACO2 as candidate genes and highlighted processes related to mitochondrial energy metabolism and synaptic function. These findings refine the genomic, tissue, and cellular context of the shared genetic architecture of MDD and ALC and provide prioritized genomic regions, cell types, and candidate genes for validation in independent populations and functional studies.

Major Depressive Disorder↗