Mariusz Butkiewicz

Rapidly progressive Alzheimer's disease features distinct structures of amyloid-β.

Genetic and environmental factors that increase the risk of late-onset Alzheimer disease are now well recognized but the cause of variable progression rates and phenotypes of sporadic Alzheimers disease is largely unknown. We aimed to investigate the relationship between diverse structural assemblies of amyloid-β and rates of clinical decline in Alzheimers disease. Using novel biophysical methods, we analysed levels, particle size, and conformational characteristics of amyloid-β in the posterior cingulate cortex, hippocampus and cerebellum of 48 cases of Alzheimers disease with distinctly different disease durations, and correlated the data with APOE gene polymorphism. In both hippocampus and posterior cingulate cortex we identified an extensive array of distinct amyloid-β42 particles that differ in size, display of N-terminal and C-terminal domains, and conformational stability. In contrast, amyloid-β40 present at low levels did not form a major particle with discernible size, and both N-terminal and C- terminal domains were largely exposed. Rapidly progressive Alzheimers disease that is associated with a low frequency of APOE e4 allele demonstrates considerably expanded conformational heterogeneity of amyloid-β42, with higher levels of distinctly structured amyloid-β42 particles composed of 30-100 monomers, and fewer particles composed of < 30 monomers. The link between rapid clinical decline and levels of amyloid-β42 with distinct structural characteristics suggests that different conformers may play an important role in the pathogenesis of distinct Alzheimers disease phenotypes. These findings indicate that Alzheimers disease exhibits a wide spectrum of amyloid-β42 structural states and imply the existence of prion-like conformational strains.

Shared Genetic Etiology of Autoimmune Diseases in Patients from a Biorepository Linked to De-identified Electronic Health Records

Autoimmune diseases represent a significant medical burden affecting up to 5–8% of the U.S. population. While genetics is known to play a role, studies of common autoimmune diseases are complicated by phenotype heterogeneity, limited sample sizes, and a single disease approach. Here we performed a targeted genetic association study for cases of multiple sclerosis (MS), rheumatoid arthritis (RA), and Crohns disease (CD) to assess which common genetic variants contribute individually and pleiotropically to disease risk. Joint modeling and pathway analysis combining the three phenotypes were performed to identify common underlying mechanisms of risk of autoimmune conditions. European American cases of MS, RA, and CD, (n = 119, 53, and 129, respectively) and 1924 controls were identified using de-identified electronic health records (EHRs) through a combination of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) billing codes, Current Procedural Terminology (CPT) codes, medication lists, and text matching. As expected, hallmark SNPs in MS, such as DQA1 rs9271366 (OR = 1.91; p = 0.008), replicated in the present study. Both MS and CD were associated with TIMMDC1 rs2293370 (OR = 0.27, p = 0.01; OR = 0.25, p = 0.02; respectively). Additionally, PDE2A rs3781913 was significantly associated with both CD and RA (OR = 0.46, p = 0.02; OR = 0.32, p = 0.02; respectively). Joint modeling and pathway analysis identified variants within the KEGG NOD-like receptor signaling pathway and Shigellosis pathway as being correlated with the combined autoimmune phenotype. Our study replicated previously-reported genetic associations for MS and CD in a population derived from de-identified EHRs. We found evidence to support a shared genetic etiology between CD/MS and CD/RA outside of the major histocompatibility complex region and identified KEGG pathways indicative of a bacterial pathogenesis risk for autoimmunity in a joint model. Future work to elucidate this shared etiology will be key in the development of risk models as envisioned in the era of precision medicine.

Genetic Variation in Genes Underlying Diverse Dementias May Explain a Small Proportion of Cases in the Alzheimer’s Disease Sequencing Project

Background/Aims: The Alzheimer’s Disease Sequencing Project (ADSP) aims to identify novel genes influencing Alzheimer’s disease (AD). Variants within genes known to cause dementias other than AD have previously been associated with AD risk. We describe evidence of co-segregation and associations between variants in dementia genes and clinically diagnosed AD within the ADSP. Methods: We summarize the properties of known pathogenic variants within dementia genes, describe the co-segregation of variants annotated as “pathogenic” in ClinVar and new candidates observed in ADSP families, and test for associations between rare variants in dementia genes in the ADSP case-control study. The participants were clinically evaluated for AD, and they represent European, Caribbean Hispanic, and isolate Dutch populations. Results/Conclusions: Pathogenic variants in dementia genes were predominantly rare and conserved coding changes. Pathogenic variants within ARSA, CSF1R, and GRN were observed, and candidate variants in GRN and CHMP2B were nominated in ADSP families. An independent case-control study provided evidence of an association between variants in TREM2, APOE, ARSA, CSF1R, PSEN1, and MAPT and risk of AD. Variants in genes which cause dementing disorders may influence the clinical diagnosis of AD in a small proportion of cases within the ADSP.

Functional annotation of genomic variants in studies of late-onset Alzheimer’s disease

Abstract Motivation Annotation of genomic variants is an increasingly important and complex part of the analysis of sequence-based genomic analyses. Computational predictions of variant function are routinely incorporated into gene-based analyses of rare-variants, though to date most studies use limited information for assessing variant function that is often agnostic of the disease being studied. Results In this work, we outline an annotation process motivated by the Alzheimer’s Disease Sequencing Project, illustrate the impact of including tissue-specific transcript sets and sources of gene regulatory information and assess the potential impact of changing genomic builds on the annotation process. While these factors only impact a small proportion of total variant annotations (∼5%), they influence the potential analysis of a large fraction of genes (∼25%). Availability and implementation Individual variant annotations are available via the NIAGADS GenomicsDB, at https://www.niagads.org/genomics/ tools-and-software/databases/genomics-database. Annotations are also available for bulk download at https://www.niagads.org/datasets. Annotation processing software is available at http://www.icompbio.net/resources/software-and-downloads/. Supplementary information Supplementary data are available at Bioinformatics online.

In Silico Functional Annotation of Genomic Variation.

This unit describes the concepts and practical techniques for annotating genomic variants in the human genome to estimate their functional significance. With the rapid increase of available whole exome and whole genome sequencing information for human studies, annotation techniques have become progressively more important for highlighting and prioritizing nucleotide variants and their potential impact on genes and other genetic constructs. Here, we present an overview of different types of variant annotation approaches and elaborate on their foundations, assumptions, and the downstream consequences of their use. Computational approaches and tools to assign annotations and to identify variants are reviewed. Further, the general philosophy of assigning potential function to a genetic change within the biological context of a disease is discussed.

Testosterone Pathway Genetic Polymorphisms in Relation to Primary Open-Angle Glaucoma: An Analysis in Two Large Datasets

Purpose Sex hormones may be associated with primary open-angle glaucoma (POAG), although the mechanisms are unclear. We previously observed that gene variants involved with estrogen metabolism were collectively associated with POAG in women but not men; here we assessed gene variants related to testosterone metabolism collectively and POAG risk. Methods We used two datasets: one from the United States (3853 cases and 33,480 controls) and another from Australia (1155 cases and 1992 controls). Both datasets contained densely called genotypes imputed to the 1000 Genomes reference panel. We used pathway- and gene-based approaches with Pathway Analysis by Randomization Incorporating Structure (PARIS) software to assess the overall association between a panel of single nucleotide polymorphisms (SNPs) in testosterone metabolism genes and POAG. In sex-stratified analyses, we evaluated POAG overall and POAG subtypes defined by maximum IOP (high-tension [HTG] or normal tension glaucoma [NTG]). Results In the US dataset, the SNP panel was not associated with POAG (permuted P = 0.77), although there was an association in the Australian sample (permuted P = 0.018). In both datasets, the SNP panel was associated with POAG in men (permuted P ≤ 0.033) and not women (permuted P ≥ 0.42), but in gene-based analyses, there was no consistency on the main genes responsible for these findings. In both datasets, the testosterone pathway association with HTG was significant (permuted P ≤ 0.011), but again, gene-based analyses showed no consistent driver gene associations. Conclusions Collectively, testosterone metabolism pathway SNPs were consistently associated with the high-tension subtype of POAG in two datasets.

Introducing COCOS: codon consequence scanner for annotating reading frame changes induced by stop-lost and frame shift variants

Abstract Summary Reading frame altering genomic variants can impact gene expression levels and the structure of protein products, thus potentially inducing disease phenotypes. Current annotation approaches report the impact of such variants in the context of altered DNA sequence only; attributes of the resulting transcript, reading frame and translated protein product are not reported. To remedy this shortcoming, we present a new genetic annotation approach termed Codon Consequence Scanner (COCOS). Implemented as an Ensembl variant effect predictor (VEP) plugin, COCOS captures amino acid sequence alterations stemming from variants that produce an altered reading frame, such as stop-lost variants and small insertions and deletions (InDels). To highlight its significance, COCOS was applied to data from the 1000 Genomes Project. Transcripts affected by stop-lost variants introduce a median of 15 amino acids, while InDels have a more extensive impact with a median of 66 amino acids being incorporated. Captured sequence alterations are written out in FASTA format and can be further analyzed for impact on the underlying protein structure. Availability and Implementation COCOS is available to all users on github: https://github.com/butkiem/COCOS

SEX-SPECIFIC ANALYSIS OF THE ADSP CASE-CONTROL WHOLE-EXOME SEQUENCING DATASET

National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, MA, USA; University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA; Universit e Lille 2, Lille, France; Institut Pasteur de Lille, Lille, France; INSERM, Lille, France; Erasmus University Medical Center, Rotterdam, Netherlands; University of Texas School of Public Health, Houston, TX, USA; University of Texas Health Science Center at Houston, Houston, TX, USA. Contact e-mail: joshbis@uw.edu