Perry G. Ridge

Rare coding variants in the phospholipase D3 gene confer risk for Alzheimer's disease

Genome-wide association studies (GWAS) have identified several risk variants for late-onset Alzheimers disease (LOAD). These common variants have replicable but small effects on LOAD risk and generally do not have obvious functional effects. Low-frequency coding variants, not detected by GWAS, are predicted to include functional variants with larger effects on risk. To identify low-frequency coding variants with large effects on LOAD risk, we carried out whole-exome sequencing (WES) in 14 large LOAD families and follow-up analyses of the candidate variants in several large LOAD case–control data sets. A rare variant in PLD3 (phospholipase D3; Val232Met) segregated with disease status in two independent families and doubled risk for Alzheimer’s disease in seven independent case–control series with a total of more than 11,000 cases and controls of European descent. Gene-based burden analyses in 4,387 cases and controls of European descent and 302 African American cases and controls, with complete sequence data for PLD3, reveal that several variants in this gene increase risk for Alzheimer’s disease in both populations. PLD3 is highly expressed in brain regions that are vulnerable to Alzheimer’s disease pathology, including hippocampus and cortex, and is expressed at significantly lower levels in neurons from Alzheimer’s disease brains compared to control brains. Overexpression of PLD3 leads to a significant decrease in intracellular amyloid-β precursor protein (APP) and extracellular Aβ42 and Aβ40 (the 42- and 40-residue isoforms of the amyloid-β peptide), and knockdown of PLD3 leads to a significant increase in extracellular Aβ42 and Aβ40. Together, our genetic and functional data indicate that carriers of PLD3 coding variants have a twofold increased risk for LOAD and that PLD3 influences APP processing. This study provides an example of how densely affected families may help to identify rare variants with large effects on risk for disease or other complex traits.

Alzheimer's disease: analyzing the missing heritability.

Alzheimer’s disease (AD) is a complex disorder influenced by environmental and genetic factors. Recent work has identified 11 AD markers in 10 loci. We used Genome-wide Complex Trait Analysis to analyze >2 million SNPs for 10,922 individuals from the Alzheimer’s Disease Genetics Consortium to assess the phenotypic variance explained first by known late-onset AD loci, and then by all SNPs in the Alzheimer’s Disease Genetics Consortium dataset. In all, 33% of total phenotypic variance is explained by all common SNPs. APOE alone explained 6% and other known markers 2%, meaning more than 25% of phenotypic variance remains unexplained by known markers, but is tagged by common SNPs included on genotyping arrays or imputed with HapMap genotypes. Novel AD markers that explain large amounts of phenotypic variance are likely to be rare and unidentifiable using genome-wide association studies. Based on our findings and the current direction of human genetics research, we suggest specific study designs for future studies to identify the remaining heritability of Alzheimer’s disease.

Association and Expression Analyses With Single-Nucleotide Polymorphisms in TOMM40 in Alzheimer Disease

BACKGROUND Apolipoprotein E (APOE) is the most statistically significant genetic risk factor for late-onset Alzheimer disease (LOAD). The linkage disequilibrium pattern around the APOE gene has made it difficult to determine whether all the association signal is derived from APOE or whether there is an independent signal from a nearby gene. OBJECTIVE To attempt to replicate a recently reported association of APOE 3-TOMM40 haplotypes with risk and age at onset. DESIGN We used standard techniques to genotype several polymorphisms in the APOE-TOMM40 region in a large case-control series, in a series with cerebrospinal fluid biomarker data, and in brain tissue. SETTING Alzheimers Disease Research Center. PARTICIPANTS Research volunteers who were cognitively normal or had Alzheimer disease. MAIN OUTCOME MEASURES Disease status and age at onset. RESULTS We did not replicate the previously reported association of the polyT polymorphism (rs10524523) with risk and age at onset. We found a significant association between rs10524523 and risk of LOAD in APOE 33 homozygotes but in the opposite direction as the previously reported association (the very long allele was underrepresented in cases vs controls in this study (P = .004]). We found no association between rs10524523 and cerebrospinal fluid tau or β-amyloid 42 levels or TOMM40 or APOE gene expression. CONCLUSIONS Although we did not replicate the earlier association between the APOE 3-TOMM40 haplotypes and age at onset, we observed that the polyT polymorphism is associated with risk of LOAD in APOE 33 homozygotes in a large case-control series but in the opposite direction as in the previous study.

Good laboratory practice for clinical next-generation sequencing informatics pipelines

Amy S Gargis, Centers for Disease Control & Prevention Lisa Kalman, Centers for Disease Control & Prevention David P Bick, Medical College of Wisconsin Cristina da Silva, Emory University David P Dimmock, Medical College of Wisconsin Birgit H Funke, Partners Healthcare Personalized Medicine Sivakumar Gowrisankar, Partners Healthcare Personalized Medicine Madhuri Hegde, Emory University Shashikant Kulkarni, Washington University Christopher E Mason, Cornell University

Genome-Wide Association Study of CSF Levels of 59 Alzheimer's Disease Candidate Proteins: Significant Associations with Proteins Involved in Amyloid Processing and Inflammation

Cerebrospinal fluid (CSF) 42 amino acid species of amyloid beta (Aβ42) and tau levels are strongly correlated with the presence of Alzheimers disease (AD) neuropathology including amyloid plaques and neurodegeneration and have been successfully used as endophenotypes for genetic studies of AD. Additional CSF analytes may also serve as useful endophenotypes that capture other aspects of AD pathophysiology. Here we have conducted a genome-wide association study of CSF levels of 59 AD-related analytes. All analytes were measured using the Rules Based Medicine Human DiscoveryMAP Panel, which includes analytes relevant to several disease-related processes. Data from two independently collected and measured datasets, the Knight Alzheimers Disease Research Center (ADRC) and Alzheimers Disease Neuroimaging Initiative (ADNI), were analyzed separately, and combined results were obtained using meta-analysis. We identified genetic associations with CSF levels of 5 proteins (Angiotensin-converting enzyme (ACE), Chemokine (C-C motif) ligand 2 (CCL2), Chemokine (C-C motif) ligand 4 (CCL4), Interleukin 6 receptor (IL6R) and Matrix metalloproteinase-3 (MMP3)) with study-wide significant p-values (p<1.46×10−10) and significant, consistent evidence for association in both the Knight ADRC and the ADNI samples. These proteins are involved in amyloid processing and pro-inflammatory signaling. SNPs associated with ACE, IL6R and MMP3 protein levels are located within the coding regions of the corresponding structural gene. The SNPs associated with CSF levels of CCL4 and CCL2 are located in known chemokine binding proteins. The genetic associations reported here are novel and suggest mechanisms for genetic control of CSF and plasma levels of these disease-related proteins. Significant SNPs in ACE and MMP3 also showed association with AD risk. Our findings suggest that these proteins/pathways may be valuable therapeutic targets for AD. Robust associations in cognitively normal individuals suggest that these SNPs also influence regulation of these proteins more generally and may therefore be relevant to other diseases.

Genetics of Alzheimer’s Disease

Alzheimers disease is the most common form of dementia and is the only top 10 cause of death in the United States that lacks disease-altering treatments. It is a complex disorder with environmental and genetic components. There are two major types of Alzheimers disease, early onset and the more common late onset. The genetics of early-onset Alzheimers disease are largely understood with variants in three different genes leading to disease. In contrast, while several common alleles associated with late-onset Alzheimers disease, including APOE, have been identified using association studies, the genetics of late-onset Alzheimers disease are not fully understood. Here we review the known genetics of early- and late-onset Alzheimers disease.

Population-based analysis of Alzheimer's disease risk alleles implicates genetic interactions.

BACKGROUND Reported odds ratios and population attributable fractions (PAF) for late-onset Alzheimers disease (LOAD) risk loci (BIN1, ABCA7, CR1, MS4A4E, CD2AP, PICALM, MS4A6A, CD33, and CLU) come from clinically ascertained samples. Little is known about the combined PAF for these LOAD risk alleles and the utility of these combined markers for case-control prediction. Here we evaluate these loci in a large population-based sample to estimate PAF and explore the effects of additive and nonadditive interactions on LOAD status prediction performance. METHODS 2419 samples from the Cache County Memory Study were genotyped for APOE and nine LOAD risk loci from AlzGene.org. We used logistic regression and receiver operator characteristic analysis to assess the LOAD status prediction performance of these loci using additive and nonadditive models and compared odds ratios and PAFs between AlzGene.org and Cache County. RESULTS Odds ratios were comparable between Cache County and AlzGene.org when identical single nucleotide polymorphisms were genotyped. PAFs from AlzGene.org ranged from 2.25% to 37%; those from Cache County ranged from .05% to 20%. Including non-APOE alleles significantly improved LOAD status prediction performance (area under the curve = .80) over APOE alone (area under the curve = .78) when not constrained to an additive relationship (p < .03). We identified potential allelic interactions (p values uncorrected): CD33-MS4A4E (synergy factor = 5.31; p < .003) and CLU-MS4A4E (synergy factor = 3.81; p < .016). CONCLUSIONS Although nonadditive interactions between loci significantly improve diagnostic ability, the improvement does not reach the desired sensitivity or specificity for clinical use. Nevertheless, these results suggest that understanding gene-gene interactions may be important in resolving Alzheimers disease etiology.

Mitochondrial Genomic Analysis of Late Onset Alzheimer’s Disease Reveals Protective Haplogroups H6A1A/H6A1B: The Cache County Study on Memory in Aging

Background Alzheimer’s disease (AD) is the most common cause of dementia and AD risk clusters within families. Part of the familial aggregation of AD is accounted for by excess maternal vs. paternal inheritance, a pattern consistent with mitochondrial inheritance. The role of specific mitochondrial DNA (mtDNA) variants and haplogroups in AD risk is uncertain. Methodology/Principal Findings We determined the complete mitochondrial genome sequence of 1007 participants in the Cache County Study on Memory in Aging, a population-based prospective cohort study of dementia in northern Utah. AD diagnoses were made with a multi-stage protocol that included clinical examination and review by a panel of clinical experts. We used TreeScanning, a statistically robust approach based on haplotype networks, to analyze the mtDNA sequence data. Participants with major mitochondrial haplotypes H6A1A and H6A1B showed a reduced risk of AD (p = 0.017, corrected for multiple comparisons). The protective haplotypes were defined by three variants: m.3915G>A, m.4727A>G, and m.9380G>A. These three variants characterize two different major haplogroups. Together m.4727A>G and m.9380G>A define H6A1, and it has been suggested m.3915G>A defines H6A. Additional variants differentiate H6A1A and H6A1B; however, none of these variants had a significant relationship with AD case-control status. Conclusions/Significance Our findings provide evidence of a reduced risk of AD for individuals with mtDNA haplotypes H6A1A and H6A1B. These findings are the results of the largest study to date with complete mtDNA genome sequence data, yet the functional significance of the associated haplotypes remains unknown and replication in others studies is necessary.

Mycobacterium chelonae-abscessus Complex Associated with Sinopulmonary Disease, Northeastern USA

Members of the Mycobacterium chelonae-abscessus complex represent Mycobacterium species that cause invasive infections in immunocompetent and immunocompromised hosts. We report the detection of a new pathogen that had been misidentified as M. chelonae with an atypical antimicrobial drug susceptibility profile. The discovery prompted a multicenter investigation of 26 patients. Almost all patients were from the northeastern United States, and most had underlying sinus or pulmonary disease. Infected patients had clinical features similar to those with M. abscessus infections. Taxonomically, the new pathogen shared molecular identity with members of the M. chelonae-abscessus complex. Multilocus DNA target sequencing, DNA-DNA hybridization, and deep multilocus sequencing (43 full-length genes) support a new taxon for these microorganisms. Because most isolates originated in Pennsylvania, we propose the name M. franklinii sp. nov. This investigation underscores the need for accurate identification of Mycobacterium spp. to detect new pathogens implicated in human disease.

Mitochondrial Haplotypes Associated with Biomarkers for Alzheimer's Disease

Various studies have suggested that the mitochondrial genome plays a role in late-onset Alzheimer’s disease, although results are mixed. We used an endophenotype-based approach to further characterize mitochondrial genetic variation and its relationship to risk markers for Alzheimer’s disease. We analyzed longitudinal data from non-demented, mild cognitive impairment, and late-onset Alzheimer’s disease participants in the Alzheimer’s Disease Neuroimaging Initiative with genetic, brain imaging, and behavioral data. We assessed the relationship of structural MRI and cognitive biomarkers with mitochondrial genome variation using TreeScanning, a haplotype-based approach that concentrates statistical power by analyzing evolutionarily meaningful groups (or clades) of haplotypes together for association with a phenotype. Four clades were associated with three different endophenotypes: whole brain volume, percent change in temporal pole thickness, and left hippocampal atrophy over two years. This is the first study of its kind to identify mitochondrial variation associated with brain imaging endophenotypes of Alzheimer’s disease. Our results provide additional evidence that the mitochondrial genome plays a role in risk for Alzheimer’s disease.