Mary Ellen Koran

Genetic interactions associated with 12-month atrophy in hippocampus and entorhinal cortex in Alzheimer's Disease Neuroimaging Initiative

Missing heritability in late onset Alzheimer disease can be attributed, at least in part, to heterogeneity in disease status and to the lack of statistical analyses exploring genetic interactions. In the current study, we use quantitative intermediate phenotypes derived from magnetic resonance imaging data available from the Alzheimers Disease Neuroimaging Initiative, and we test for association with gene-gene interactions within biological pathways. Regional brain volumes from the hippocampus (HIP) and entorhinal cortex (EC) were estimated from baseline and 12-month magnetic resonance imaging scans. Approximately 560,000 single nucleotide polymorphisms (SNPs) were available genome-wide. We tested all pairwise SNP-SNP interactions (approximately 151 million) within 212 Kyoto Encyclopedia of Genes and Genomes pathways for association with 12-month regional atrophy rates using linear regression, with sex, APOE ε4 carrier status, age, education, and clinical status as covariates. A total of 109 SNP-SNP interactions were associated with right HIP atrophy, and 125 were associated with right EC atrophy. Enrichment analysis indicated significant SNP-SNP interactions were overrepresented in the calcium signaling and axon guidance pathways for both HIP and EC atrophy and in the ErbB signaling pathway for HIP atrophy.

Associations between KCNJ6 (GIRK2) gene polymorphisms and pain-related phenotypes.

Summary Variations in the KCNJ6 gene appear to influence both acute and chronic pain phenotypes. Abstract G‐protein coupled inwardly rectifying potassium (GIRK) channels are effectors determining degree of analgesia experienced upon opioid receptor activation by endogenous and exogenous opioids. The impact of GIRK‐related genetic variation on human pain responses has received little research attention. We used a tag single nucleotide polymorphism (SNP) approach to comprehensively examine pain‐related effects of KCNJ3 (GIRK1) and KCNJ6 (GIRK2) gene variation. Forty‐one KCNJ3 and 69 KCNJ6 tag SNPs were selected, capturing the known variability in each gene. The primary sample included 311 white patients undergoing total knee arthroplasty in whom postsurgical oral opioid analgesic medication order data were available. Primary sample findings were then replicated in an independent white sample of 63 healthy pain‐free individuals and 75 individuals with chronic low back pain (CLBP) who provided data regarding laboratory acute pain responsiveness (ischemic task) and chronic pain intensity and unpleasantness (CLBP only). Univariate quantitative trait analyses in the primary sample revealed that 8 KCNJ6 SNPs were significantly associated with the medication order phenotype (P < .05); overall effects of the KCNJ6 gene (gene set‐based analysis) just failed to reach significance (P = .054). No significant KCNJ3 effects were observed. A continuous GIRK Related Risk Score (GRRS) was derived in the primary sample to summarize each individual’s number of KCNJ6 “pain risk” alleles. This GRRS was applied to the replication sample, which revealed significant associations (P < .05) between higher GRRS values and lower acute pain tolerance and higher CLBP intensity and unpleasantness. Results suggest further exploration of the impact of KCNJ6 genetic variation on pain outcomes is warranted.

Genetic interactions found between calcium channel genes modulate amyloid load measured by positron emission tomography.

Late-onset Alzheimer’s disease (LOAD) is known to have a complex, oligogenic etiology, with considerable genetic heterogeneity. We investigated the influence of genetic interactions between genes in the Alzheimer’s disease (AD) pathway on amyloid-beta (Aβ) deposition as measured by PiB or AV-45 ligand positron emission tomography (PET) to aid in understanding LOAD’s genetic etiology. Subsets of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohorts were used for discovery and for two independent validation analyses. A significant interaction between RYR3 and CACNA1C was confirmed in all three of the independent ADNI datasets. Both genes encode calcium channels expressed in the brain. The results shown here support previous animal studies implicating interactions between these calcium channels in amyloidogenesis and suggest that the pathological cascade of this disease may be modified by interactions in the amyloid–calcium axis. Future work focusing on the mechanisms of such relationships may inform targets for clinical intervention.

Epistatic genetic effects among Alzheimer's candidate genes.

Background Novel risk variants for late-onset Alzheimer’s disease (AD) have been identified and replicated in genome-wide association studies. Recent work has begun to address the relationship between these risk variants and biomarkers of AD, though results have been mixed. The aim of the current study was to characterize single marker and epistatic genetic effects between the top candidate Single Nucleotide Polymorphisms (SNPs) in relation to amyloid deposition. Methods We used a combined dataset across ADNI-1 and ADNI-2, and looked within each dataset separately to validate identified genetic effects. Amyloid was quantified using data acquired by Positron Emission Tomography (PET) with 18F-AV-45. Results Two SNP-SNP interactions reached significance when correcting for multiple comparisons, BIN1 (rs7561528, rs744373) x PICALM (rs7851179). Carrying the minor allele in BIN1 was related to higher levels of amyloid deposition, however only in non-carriers of the protective PICALM minor allele. Conclusions Our results support previous research suggesting these candidate SNPs do not show single marker associations with amyloid pathology. However, we provide evidence for a novel interaction between PICALM and BIN1 in relation to amyloid deposition. Risk related to the BIN1 minor allele appears to be mitigated in the presence of the PICALM protective variant. In that way, variance in amyloid plaque burden can be better classified within the context of a complex genetic background. Efforts to model cumulative risk for AD should explicitly account for this epistatic effect, and future studies should explicitly test for such effects whenever statistically feasible.

Interactions between GSK3β and amyloid genes explain variance in amyloid burden

The driving theoretical framework of Alzheimers disease (AD) has been built around the amyloid-β (Aβ) cascade in which amyloid pathology precedes and drives tau pathology. Other evidence has suggested that tau and amyloid pathology may arise independently. Both lines of research suggest that there may be epistatic relationships between genes involved in amyloid and tau pathophysiology. In the current study, we hypothesized that genes coding glycogen synthase kinase 3 (GSK-3) and comparable tau kinases would modify genetic risk for amyloid plaque pathology. Quantitative amyloid positron emission tomography data from the Alzheimers Disease Neuroimaging Initiative served as the quantitative outcome in regression analyses, covarying for age, gender, and diagnosis. Three interactions reached statistical significance, all involving the GSK3β single nucleotide polymorphism rs334543-2 with APBB2 (rs2585590, rs3098914) and 1 with APP (rs457581). These interactions explained 1.2%, 1.5%, and 1.5% of the variance in amyloid deposition respectively. Our results add to a growing literature on the role of GSK-3 activity in amyloid processing and suggest that combined variation in GSK3β and APP-related genes may result in increased amyloid burden.

Differences in age-related effects on brain volume in Down syndrome as compared to Williams syndrome and typical development

BackgroundIndividuals with Down Syndrome (DS) are reported to experience early onset of brain aging. However, it is not well understood how pre-existing neurodevelopmental effects versus neurodegenerative processes might be contributing to the observed pattern of brain atrophy in younger adults with DS. The aims of the current study were to: (1) to confirm previous findings of age-related changes in DS compared to adults with typical development (TD), (2) to test for an effect of these age-related changes in a second neurodevelopmental disorder, Williams syndrome (WS), and (3) to identify a pattern of regional age-related effects that are unique to DS.MethodsHigh-resolution T1-weighted MRI of the brains of subjects with DS, WS, and TD controls were segmented, and estimates of regional brain volume were derived using FreeSurfer. A general linear model was employed to test for age-related effects on volume between groups. Secondary analyses in the DS group explored the relationship between brain volume and neuropsychological tests and APOE.ResultsConsistent with previous findings, the DS group showed significantly greater age-related effects relative to TD controls in total gray matter and in regions of the orbitofrontal cortex and the parietal cortex. Individuals with DS also showed significantly greater age-related effects on volume of the left and right inferior lateral ventricles (LILV and RILV, respectively). There were no significant differences in age-related effects on volume when comparing the WS and TD groups. In the DS group, cognitive tests scores measuring signs of dementia and APOE ϵ4 carrier status were associated with LILV and RILV volume.ConclusionsIndividuals with DS demonstrated a unique pattern of age-related effects on gray matter and ventricular volume, the latter of which was associated with dementia rating scores in the DS group. Results may indicate that early onset of brain aging in DS is primarily due to DS-specific neurodegenerative processes, as opposed to general atypical neurodevelopment.

Genetic Interactions within Inositol-Related Pathways are Associated with Longitudinal Changes in Ventricle Size

The genetic etiology of late-onset Alzheimers disease (LOAD) has proven complex, involving clinical and genetic heterogeneity and gene-gene interactions. Recent genome wide association studies in LOAD have led to the discovery of novel genetic risk factors; however, the investigation of gene-gene interactions has been limited. Conventional genetic studies often use binary disease status as the primary phenotype, but for complex brain-based diseases, neuroimaging data can serve as quantitative endophenotypes that correlate with disease status and closely reflect pathological changes. In the Alzheimers Disease Neuroimaging Initiative cohort, we tested for association of genetic interactions with longitudinal MRI measurements of the inferior lateral ventricles (ILVs), which have repeatedly shown a relationship to LOAD status and progression. We performed linear regression to evaluate the ability of pathway-derived SNP-SNP pairs to predict the slope of change in volume of the ILVs. After Bonferroni correction, we identified four significant interactions in the right ILV (RILV) corresponding to gene-gene pairs SYNJ2-PI4KA, PARD3-MYH2, PDE3A-ABHD12B, and OR2L13-PRKG1 and one significant interaction in the left ILV (LILV) corresponding to SYNJ2-PI4KA. The SNP-SNP interaction corresponding to SYNJ2-PI4KA was identical in the RILV and LILV and was the most significant interaction in each (RILV: p = 9.13 × 10(-12); LILV: p = 8.17 × 10(-13)). Both genes belong to the inositol phosphate signaling pathway which has been previously associated with neurodegeneration in AD and we discuss the possibility that perturbation of this pathway results in a down-regulation of the Akt cell survival pathway and, thereby, decreased neuronal survival, as reflected by increased volume of the ventricles.

Genetic modification of the relationship between phosphorylated tau and neurodegeneration

A subset of individuals present at autopsy with the pathologic features of Alzheimers disease having never manifest the clinical symptoms. We sought to identify genetic factors that modify the relationship between phosphorylated tau (PTau) and dilation of the lateral inferior ventricles.

Impact of family structure and common environment on heritability estimation for neuroimaging genetics studies using Sequential Oligogenic Linkage Analysis Routines

Abstract. Imaging genetics is an emerging methodological field that combines genetic information with medical imaging-derived metrics to understand how genetic factors impact observable phenotypes. In order for a trait to be a reasonable phenotype in an imaging genetics study, it must be heritable: at least some proportion of its variance must be due to genetic influences. The Sequential Oligogenic Linkage Analysis Routines (SOLAR) imaging genetics software can estimate the heritability of a trait in complex pedigrees. We investigate the ability of SOLAR to accurately estimate heritability and common environmental effects on simulated imaging phenotypes in various family structures. We found that heritability is reliably estimated with small family-based studies of 40 to 80 individuals, though subtle differences remain between the family structures. In an imaging application analysis, we found that with 80 subjects in any of the family structures, estimated heritability of white matter fractional anisotropy was biased by <10% for every region of interest. Results from these studies can be used when investigators are evaluating power in planning genetic analyzes.

Genetic variation modifies risk for neurodegeneration based on biomarker status.

Background: While a great deal of work has gone into understanding the relationship between Cerebrospinal fluid (CSF) biomarkers, brain atrophy, and disease progression, less work has attempted to investigate how genetic variation modifies these relationships. The goal of this study was two-fold. First, we sought to identify high-risk vs. low-risk individuals based on their CSF tau and Aβ load and characterize these individuals with regard to brain atrophy in an AD-relevant region of interest. Next, we sought to identify genetic variants that modified the relationship between biomarker classification and neurodegeneration. Methods: Participants were categorized based on established cut-points for biomarker positivity. Mixed model regression was used to quantify longitudinal change in the left inferior lateral ventricle. Interaction analyses between single nucleotide polymorphisms (SNPs) and biomarker group status were performed using a genome wide association study (GWAS) approach. Correction for multiple comparisons was performed using the Bonferroni procedure. Results: One intergenic SNP (rs4866650) and one SNP within the SPTLC1 gene (rs7849530) modified the association between amyloid positivity and neurodegeneration. A transcript variant of WDR11-AS1 gene (rs12261764) modified the association between tau positivity and neurodegeneration. These effects were consistent across the two sub-datasets and explained approximately 3% of variance in ventricular dilation. One additional SNP (rs6887649) modified the association between amyloid positivity and baseline ventricular volume, but was not observed consistently across the sub-datasets. Conclusions: Genetic variation modifies the association between AD biomarkers and neurodegeneration. Genes that regulate the molecular response in the brain to oxidative stress may be particularly relevant to neural vulnerability to the damaging effects of amyloid-β.