In vivo validation of late-onset Alzheimer's disease genetic risk factors.

Introduction: Genome-wide association studies have identified over 70 genetic loci associated with late-onset Alzheimer's disease (LOAD), but few candidate polymorphisms have been functionally assessed for disease relevance and mechanism of action.

Methods: Candidate genetic risk variants were informatically prioritized and individually engineered into a LOAD-sensitized mouse model that carries the AD risk variants APOE ε4/ε4 and Trem2*R47H. The potential disease relevance of each model was assessed by comparing brain transcriptomes measured with the Nanostring Mouse AD Panel at 4 and 12 months of age with human study cohorts.

Genetically diverse mouse models of SARS-CoV-2 infection reproduce clinical variation in type I interferon and cytokine responses in COVID-19.

Inflammation in response to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection drives severity of coronavirus disease 2019 (COVID-19) and is influenced by host genetics. To understand mechanisms of inflammation, animal models that reflect genetic diversity and clinical outcomes observed in humans are needed. We report a mouse panel comprising the genetically diverse Collaborative Cross (CC) founder strains crossed to human ACE2 transgenic mice (K18-hACE2) that confers susceptibility to SARS-CoV-2.

A novel human tau knock-in mouse model reveals interaction of Abeta and human tau under progressing cerebral amyloidosis in 5xFAD mice.

Background: Hyperphosphorylation and intraneuronal aggregation of the microtubule-associated protein tau is a major pathological hallmark of Alzheimer's disease (AD) brain. Of special interest is the effect of cerebral amyloid beta deposition, the second main hallmark of AD, on human tau pathology. Therefore, studying the influence of cerebral amyloidosis on human tau in a novel human tau knock-in (htau-KI) mouse model could help to reveal new details on their interplay.

Genetically diverse mouse models of SARS-CoV-2 infection reproduce clinical variation in type I interferon and cytokine responses in COVID-19.

Inflammation in response to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection drives severity of coronavirus disease 2019 (COVID-19) and is influenced by host genetics. To understand mechanisms of inflammation, animal models that reflect genetic diversity and clinical outcomes observed in humans are needed. We report a mouse panel comprising the genetically diverse Collaborative Cross (CC) founder strains crossed to human ACE2 transgenic mice (K18-hACE2) that confers susceptibility to SARS-CoV-2.

Common Genetic Variants Contribute to Risk of Transposition of the Great Arteries.

Rationale: Dextro-transposition of the great arteries (D-TGA) is a severe congenital heart defect which affects approximately 1 in 4,000 live births. While there are several reports of D-TGA patients with rare variants in individual genes, the majority of D-TGA cases remain genetically elusive. Familial recurrence patterns and the observation that most cases with D-TGA are sporadic suggest a polygenic inheritance for the disorder, yet this remains unexplored.

Transfer learning-trained convolutional neural networks identify novel MRI biomarkers of Alzheimer's disease progression.

Introduction: Genome-wide association studies (GWAS) for late onset Alzheimer's disease (AD) may miss genetic variants relevant for delineating disease stages when using clinically defined case/control as a phenotype due to its loose definition and heterogeneity.

Methods: We use a transfer learning technique to train three-dimensional convolutional neural network (CNN) models based on structural magnetic resonance imaging (MRI) from the screening stage in the Alzheimer's Disease Neuroimaging Initiative consortium to derive image features that reflect AD progression.

Results: CNN-derived image phenotypes are significantly associated with fasting metabolites related to early lipid metabolic changes as well as insulin resistance and with genetic variants mapped to candidate genes enriched for amyloid beta degradation, tau phosphorylation, calcium ion binding-dependent synaptic loss, -regulated inflammation response, and insulin resistance.

Author Correction: Molecular estimation of neurodegeneration pseudotime in older brains.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-020-20261-6.

Molecular estimation of neurodegeneration pseudotime in older brains.

The temporal molecular changes that lead to disease onset and progression in Alzheimer's disease (AD) are still unknown. Here we develop a temporal model for these unobserved molecular changes with a manifold learning method applied to RNA-Seq data collected from human postmortem brain samples collected within the ROS/MAP and Mayo Clinic RNA-Seq studies. We define an ordering across samples based on their similarity in gene expression and use this ordering to estimate the molecular disease stage-or disease pseudotime-for each sample.

A novel systems biology approach to evaluate mouse models of late-onset Alzheimer's disease.

Background: Late-onset Alzheimer's disease (LOAD) is the most common form of dementia worldwide. To date, animal models of Alzheimer's have focused on rare familial mutations, due to a lack of frank neuropathology from models based on common disease genes. Recent multi-cohort studies of postmortem human brain transcriptomes have identified a set of 30 gene co-expression modules associated with LOAD, providing a molecular catalog of relevant endophenotypes.

Meta-Analysis of the Alzheimer's Disease Human Brain Transcriptome and Functional Dissection in Mouse Models.

We present a consensus atlas of the human brain transcriptome in Alzheimer's disease (AD), based on meta-analysis of differential gene expression in 2,114 postmortem samples. We discover 30 brain coexpression modules from seven regions as the major source of AD transcriptional perturbations. We next examine overlap with 251 brain differentially expressed gene sets from mouse models of AD and other neurodegenerative disorders.

Transcriptomic stratification of late-onset Alzheimer's cases reveals novel genetic modifiers of disease pathology.

Late-Onset Alzheimer's disease (LOAD) is a common, complex genetic disorder well-known for its heterogeneous pathology. The genetic heterogeneity underlying common, complex diseases poses a major challenge for targeted therapies and the identification of novel disease-associated variants. Case-control approaches are often limited to examining a specific outcome in a group of heterogenous patients with different clinical characteristics.

Genetic perturbations of disease risk genes in mice capture transcriptomic signatures of late-onset Alzheimer's disease.

Background: New genetic and genomic resources have identified multiple genetic risk factors for late-onset Alzheimer's disease (LOAD) and characterized this common dementia at the molecular level. Experimental studies in model organisms can validate these associations and elucidate the links between specific genetic factors and transcriptomic signatures. Animal models based on LOAD-associated genes can potentially connect common genetic variation with LOAD transcriptomes, thereby providing novel insights into basic biological mechanisms underlying the disease.

Loss of ADAMTS19 causes progressive non-syndromic heart valve disease.

Valvular heart disease is observed in approximately 2% of the general population. Although the initial observation is often localized (for example, to the aortic or mitral valve), disease manifestations are regularly observed in the other valves and patients frequently require surgery. Despite the high frequency of heart valve disease, only a handful of genes have so far been identified as the monogenic causes of disease.

Identifying and ranking potential driver genes of Alzheimer's disease using multiview evidence aggregation.

Motivation: Late onset Alzheimer's disease is currently a disease with no known effective treatment options. To better understand disease, new multi-omic data-sets have recently been generated with the goal of identifying molecular causes of disease. However, most analytic studies using these datasets focus on uni-modal analysis of the data.

Meox2 Haploinsufficiency Accelerates Axonal Degeneration in DBA/2J Glaucoma.

Purpose: Glaucoma is a complex disease with major risk factors including advancing age and increased intraocular pressure (IOP). Dissecting these earliest events will likely identify new avenues for therapeutics. Previously, we performed transcriptional profiling in DBA/2J (D2) mice, a widely used mouse model relevant to glaucoma.

Enhancing face validity of mouse models of Alzheimer's disease with natural genetic variation.

Classical laboratory strains show limited genetic diversity and do not harness natural genetic variation. Mouse models relevant to Alzheimer's disease (AD) have largely been developed using these classical laboratory strains, such as C57BL/6J (B6), and this has likely contributed to the failure of translation of findings from mice to the clinic. Therefore, here we test the potential for natural genetic variation to enhance the translatability of AD mouse models.

Variable outcomes of human heart attack recapitulated in genetically diverse mice.

Clinical variation in patient responses to myocardial infarction (MI) has been difficult to model in laboratory animals. To assess the genetic basis of variation in outcomes after heart attack, we characterized responses to acute MI in the Collaborative Cross (CC), a multi-parental panel of genetically diverse mouse strains. Striking differences in post-MI functional, morphological, and myocardial scar features were detected across 32 CC founder and recombinant inbred strains.

Copy number variation analysis in bicuspid aortic valve-related aortopathy identifies TBX20 as a contributing gene.

Bicuspid aortic valve (BAV) is the most common congenital heart defect (CHD), affecting 1-2% of the population. BAV is associated with thoracic aortic aneurysms (TAAs). Deleterious copy number variations (CNVs) were found previously in up to 10% of CHD cases.

Inferring Transmission Histories of Rare Alleles in Population-Scale Genealogies.

Learning the transmission history of alleles through a family or population plays an important role in evolutionary, demographic, and medical genetic studies. Most classical models of population genetics have attempted to do so under the assumption that the genealogy of a population is unavailable and that its idiosyncrasies can be described by a small number of parameters describing population size and mate choice dynamics. Large genetic samples have increased sensitivity to such modeling assumptions, and large-scale genealogical datasets become a useful tool to investigate realistic genealogies.

ROBO4 variants predispose individuals to bicuspid aortic valve and thoracic aortic aneurysm.

Bicuspid aortic valve (BAV) is a common congenital heart defect (population incidence, 1-2%) that frequently presents with ascending aortic aneurysm (AscAA). BAV/AscAA shows autosomal dominant inheritance with incomplete penetrance and male predominance. Causative gene mutations (for example, NOTCH1, SMAD6) are known for ≤1% of nonsyndromic BAV cases with and without AscAA, impeding mechanistic insight and development of therapeutic strategies.

Corrigendum: Candidate Gene Resequencing in a Large Bicuspid Aortic Valve-Associated Thoracic Aortic Aneurysm Cohort: as an Important Contributor.

[This corrects the article on p. 400 in vol. 8, PMID: 28659821.

Candidate Gene Resequencing in a Large Bicuspid Aortic Valve-Associated Thoracic Aortic Aneurysm Cohort: as an Important Contributor.

Bicuspid aortic valve (BAV) is the most common congenital heart defect. Although many BAV patients remain asymptomatic, at least 20% develop thoracic aortic aneurysm (TAA). Historically, BAV-related TAA was considered as a hemodynamic consequence of the valve defect.

Epistatic interaction between the lipase-encoding genes Pnpla2 and Lipe causes liposarcoma in mice.

Liposarcoma is an often fatal cancer of fat cells. Mechanisms of liposarcoma development are incompletely understood. The cleavage of fatty acids from acylglycerols (lipolysis) has been implicated in cancer.

Family Based Whole Exome Sequencing Reveals the Multifaceted Role of Notch Signaling in Congenital Heart Disease.

Left-ventricular outflow tract obstructions (LVOTO) encompass a wide spectrum of phenotypically heterogeneous heart malformations which frequently cluster in families. We performed family based whole-exome and targeted re-sequencing on 182 individuals from 51 families with multiple affected members. Central to our approach is the family unit which serves as a reference to identify causal genotype-phenotype correlations.