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Molecular Neurobiology Sep 2022Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) primarily affect the motor and frontotemporal areas of the brain, respectively. These disorders... (Review)
Review
Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) primarily affect the motor and frontotemporal areas of the brain, respectively. These disorders share clinical, genetic, and pathological similarities, and approximately 10-15% of ALS-FTD cases are considered to be multisystemic. ALS-FTD overlaps have been linked to families carrying an expansion in the intron of C9orf72 along with inclusions of TDP-43 in the brain. Other overlapping genes (VCP, FUS, SQSTM1, TBK1, CHCHD10) are also involved in similar functions that include RNA processing, autophagy, proteasome response, protein aggregation, and intracellular trafficking. Recent advances in genome sequencing have identified new genes that are involved in these disorders (TBK1, CCNF, GLT8D1, KIF5A, NEK1, C21orf2, TBP, CTSF, MFSD8, DNAJC7). Additional risk factors and modifiers have been also identified in genome-wide association studies and array-based studies. However, the newly identified genes show higher disease frequencies in combination with known genes that are implicated in pathogenesis, thus indicating probable digenetic/polygenic inheritance models, along with epistatic interactions. Studies suggest that these genes play a pleiotropic effect on ALS-FTD and other diseases such as Alzheimer's disease, Ataxia, and Parkinsonism. Besides, there have been numerous improvements in the genotype-phenotype correlations as well as clinical trials on stem cell and gene-based therapies. This review discusses the possible genetic models of ALS and FTD, the latest therapeutics, and signaling pathways involved in ALS-FTD.
Topics: Amyotrophic Lateral Sclerosis; Frontotemporal Dementia; Genetic Association Studies; Genome-Wide Association Study; Heat-Shock Proteins; Humans; Kinesins; Membrane Transport Proteins; Mitochondrial Proteins; Molecular Chaperones; Multifactorial Inheritance; Mutation
PubMed: 35768750
DOI: 10.1007/s12035-022-02934-z -
Nature Genetics Sep 2019After a decade of genome-wide association studies (GWASs), fundamental questions in human genetics, such as the extent of pleiotropy across the genome and variation in...
After a decade of genome-wide association studies (GWASs), fundamental questions in human genetics, such as the extent of pleiotropy across the genome and variation in genetic architecture across traits, are still unanswered. The current availability of hundreds of GWASs provides a unique opportunity to address these questions. We systematically analyzed 4,155 publicly available GWASs. For a subset of well-powered GWASs on 558 traits, we provide an extensive overview of pleiotropy and genetic architecture. We show that trait-associated loci cover more than half of the genome, and 90% of these overlap with loci from multiple traits. We find that potential causal variants are enriched in coding and flanking regions, as well as in regulatory elements, and show variation in polygenicity and discoverability of traits. Our results provide insights into how genetic variation contributes to trait variation. All GWAS results can be queried and visualized at the GWAS ATLAS resource ( https://atlas.ctglab.nl ).
Topics: Genetic Pleiotropy; Genetics, Population; Genome-Wide Association Study; Humans; Multifactorial Inheritance; Phenotype; Polymorphism, Single Nucleotide; Quantitative Trait Loci
PubMed: 31427789
DOI: 10.1038/s41588-019-0481-0 -
Monographs in Oral Science 2021In humans, traits and diseases are inherited primarily by complex or multifactorial modes. These imply that contributions come from more than one gene, and these can be... (Review)
Review
In humans, traits and diseases are inherited primarily by complex or multifactorial modes. These imply that contributions come from more than one gene, and these can be influenced by the environment. They are the mechanisms that underlie inheritance of dental caries, erosive tooth wear, and amelogenesis. Major gene effects (monogenic or Mendelian inheritance) and chromosomal abnormalities explain the scenarios that do not fit well with complex or multifactorial inheritance. Furthermore, there are numerous non-traditional modes of inheritance. These are all exceptions of the most common complex modes of inheritance, and their understanding is important for a number of relatively rare scenarios in humans. In this chapter, these modes of inheritance are presented, and some rare conditions are explored to highlight the relevance of studying rare diseases for the understanding of more common diseases that affect populations, using dental caries as a model.
Topics: Dental Caries; Humans; Multifactorial Inheritance; Phenotype; Tooth Attrition; Tooth Wear
PubMed: 35078172
DOI: 10.1159/000520765 -
Nature Genetics Nov 2020Here, we present a joint-tissue imputation (JTI) approach and a Mendelian randomization framework for causal inference, MR-JTI. JTI borrows information across... (Comparative Study)
Comparative Study
Here, we present a joint-tissue imputation (JTI) approach and a Mendelian randomization framework for causal inference, MR-JTI. JTI borrows information across transcriptomes of different tissues, leveraging shared genetic regulation, to improve prediction performance in a tissue-dependent manner. Notably, JTI includes the single-tissue imputation method PrediXcan as a special case and outperforms other single-tissue approaches (the Bayesian sparse linear mixed model and Dirichlet process regression). MR-JTI models variant-level heterogeneity (primarily due to horizontal pleiotropy, addressing a major challenge of transcriptome-wide association study interpretation) and performs causal inference with type I error control. We make explicit the connection between the genetic architecture of gene expression and of complex traits and the suitability of Mendelian randomization as a causal inference strategy for transcriptome-wide association studies. We provide a resource of imputation models generated from GTEx and PsychENCODE panels. Analysis of biobanks and meta-analysis data, and extensive simulations show substantially improved statistical power, replication and causal mapping rate for JTI relative to existing approaches.
Topics: Animals; Gene Expression Profiling; Genetic Association Studies; Humans; Lipoproteins, LDL; Mendelian Randomization Analysis; Mice; Models, Genetic; Multifactorial Inheritance; Predictive Value of Tests
PubMed: 33020666
DOI: 10.1038/s41588-020-0706-2 -
Current Protocols in Human Genetics Dec 2019Genome-wide variation data with millions of genetic markers have become commonplace. However, the potential for interpretation and application of these data for clinical... (Review)
Review
Genome-wide variation data with millions of genetic markers have become commonplace. However, the potential for interpretation and application of these data for clinical assessment of outcomes of interest, and prediction of disease risk, is currently not fully realized. Many common complex diseases now have numerous, well-established risk loci and likely harbor many genetic determinants with effects too small to be detected at genome-wide levels of statistical significance. A simple and intuitive approach for converting genetic data to a predictive measure of disease susceptibility is to aggregate the effects of these loci into a single measure, the genetic risk score. Here, we describe some common methods and software packages for calculating genetic risk scores and polygenic risk scores, with focus on studies of common complex diseases. We review the basic information needed, as well as important considerations for constructing genetic risk scores, including specific requirements for phenotypic and genetic data, and limitations in their application. © 2019 by John Wiley & Sons, Inc.
Topics: Disease; Genetic Markers; Genetic Predisposition to Disease; Genotype; Humans; Multifactorial Inheritance; Phenotype; Risk Factors; Software
PubMed: 31765077
DOI: 10.1002/cphg.95 -
Nature Genetics Oct 2022Single-cell RNA sequencing (scRNA-seq) provides unique insights into the pathology and cellular origin of disease. We introduce single-cell disease relevance score...
Single-cell RNA sequencing (scRNA-seq) provides unique insights into the pathology and cellular origin of disease. We introduce single-cell disease relevance score (scDRS), an approach that links scRNA-seq with polygenic disease risk at single-cell resolution, independent of annotated cell types. scDRS identifies cells exhibiting excess expression across disease-associated genes implicated by genome-wide association studies (GWASs). We applied scDRS to 74 diseases/traits and 1.3 million single-cell gene-expression profiles across 31 tissues/organs. Cell-type-level results broadly recapitulated known cell-type-disease associations. Individual-cell-level results identified subpopulations of disease-associated cells not captured by existing cell-type labels, including T cell subpopulations associated with inflammatory bowel disease, partially characterized by their effector-like states; neuron subpopulations associated with schizophrenia, partially characterized by their spatial locations; and hepatocyte subpopulations associated with triglyceride levels, partially characterized by their higher ploidy levels. Genes whose expression was correlated with the scDRS score across cells (reflecting coexpression with GWAS disease-associated genes) were strongly enriched for gold-standard drug target and Mendelian disease genes.
Topics: Gene Expression Profiling; Genome-Wide Association Study; Multifactorial Inheritance; RNA-Seq; Single-Cell Analysis; Triglycerides
PubMed: 36050550
DOI: 10.1038/s41588-022-01167-z -
Nature Genetics Sep 2022The genetic etiology of autism spectrum disorder (ASD) is multifactorial, but how combinations of genetic factors determine risk is unclear. In a large family sample, we...
The genetic etiology of autism spectrum disorder (ASD) is multifactorial, but how combinations of genetic factors determine risk is unclear. In a large family sample, we show that genetic loads of rare and polygenic risk are inversely correlated in cases and greater in females than in males, consistent with a liability threshold that differs by sex. De novo mutations (DNMs), rare inherited variants and polygenic scores were associated with various dimensions of symptom severity in children and parents. Parental age effects on risk for ASD in offspring were attributable to a combination of genetic mechanisms, including DNMs that accumulate in the paternal germline and inherited risk that influences behavior in parents. Genes implicated by rare variants were enriched in excitatory and inhibitory neurons compared with genes implicated by common variants. Our results suggest that a phenotypic spectrum of ASD is attributable to a spectrum of genetic factors that impact different neurodevelopmental processes.
Topics: Autism Spectrum Disorder; Autistic Disorder; Child; Family; Female; Genetic Predisposition to Disease; Humans; Male; Multifactorial Inheritance
PubMed: 35654974
DOI: 10.1038/s41588-022-01064-5 -
Proceedings of the National Academy of... Aug 2023Autism spectrum disorder (ASD) has a complex genetic architecture involving contributions from both de novo and inherited variation. Few studies have been designed to...
Autism spectrum disorder (ASD) has a complex genetic architecture involving contributions from both de novo and inherited variation. Few studies have been designed to address the role of rare inherited variation or its interaction with common polygenic risk in ASD. Here, we performed whole-genome sequencing of the largest cohort of multiplex families to date, consisting of 4,551 individuals in 1,004 families having two or more autistic children. Using this study design, we identify seven previously unrecognized ASD risk genes supported by a majority of rare inherited variants, finding support for a total of 74 genes in our cohort and a total of 152 genes after combined analysis with other studies. Autistic children from multiplex families demonstrate an increased burden of rare inherited protein-truncating variants in known ASD risk genes. We also find that ASD polygenic score (PGS) is overtransmitted from nonautistic parents to autistic children who also harbor rare inherited variants, consistent with combinatorial effects in the offspring, which may explain the reduced penetrance of these rare variants in parents. We also observe that in addition to social dysfunction, language delay is associated with ASD PGS overtransmission. These results are consistent with an additive complex genetic risk architecture of ASD involving rare and common variation and further suggest that language delay is a core biological feature of ASD.
Topics: Child; Humans; Autism Spectrum Disorder; Multifactorial Inheritance; Parents; Whole Genome Sequencing; Language Development Disorders; Genetic Predisposition to Disease
PubMed: 37506195
DOI: 10.1073/pnas.2215632120 -
Neuron Nov 2023Naomi Wray works at the interface of genetics, statistics and psychiatric disorders. With early training in quantitative genetics applied to livestock she brought to the...
Naomi Wray works at the interface of genetics, statistics and psychiatric disorders. With early training in quantitative genetics applied to livestock she brought to the field a perspective on the polygenic nature of common, complex disease. She advocates for experimental paradigms that exploit polygenicity to advance translational outcomes in psychiatry.
Topics: Female; Humans; Mental Disorders; Psychiatry; Multifactorial Inheritance
PubMed: 37918354
DOI: 10.1016/j.neuron.2023.09.001 -
The American Journal of Psychiatry Aug 2019
Topics: Adolescent; Depression; Depressive Disorder; Humans; Multifactorial Inheritance
PubMed: 31366223
DOI: 10.1176/appi.ajp.2019.19060590