Gene-based GWAS and biological pathway analysis of the resilience of executive functioning

The concept of resilience to Alzheimer's Disease: current definitions and cellular and molecular mechanisms

Some individuals are able to maintain their cognitive abilities despite the presence of significant Alzheimer's Disease (AD) neuropathological changes. This discrepancy between cognition and pathology has been labeled as resilience and has evolved into a widely debated concept. External factors such as cognitive stimulation are associated with resilience to AD, but the exact cellular and molecular underpinnings are not completely understood. In this review, we discuss the current definitions used in the field, highlight the translational approaches used to investigate resilience to AD and summarize the underlying cellular and molecular substrates of resilience that have been derived from human and animal studies, which have received more and more attention in the last few years. From these studies the picture emerges that resilient individuals are different from AD patients in terms of specific pathological species and their cellular reaction to AD pathology, which possibly helps to maintain cognition up to a certain tipping point. Studying these rare resilient individuals can be of great importance as it could pave the way to novel therapeutic avenues for AD.

DNA methylation signature of psychological resilience in young adults: Constructing a methylation risk score using a machine learning method

Resilience is a process associated with the ability to recover from stress and adversity. We aimed to explore the resilience-associated DNA methylation signatures and evaluate the abilities of methylation risk scores to discriminate low resilience (LR) individuals. The study recruited 78 young adults and used Connor-Davidson Resilience Scale (CD-RISC) to divide them into low and high resilience groups. We randomly allocated all participants of two groups to the discovery and validation sets. We used the blood DNA of the subjects to conduct a genome-wide methylation scan and identify the significant methylation differences of CpG Sites in the discovery set. Moreover, the classification accuracy of the DNA methylation probes was confirmed in the validation set by real-time quantitative methylation-specific polymerase chain reaction. In the genome-wide methylation profiling between LR and HR individuals, seventeen significantly differentially methylated probes were detected. In the validation set, nine DNA methylation signatures within gene coding regions were selected for verification. Finally, three methylation probes [cg18565204 (AARS), cg17682313 (FBXW7), and cg07167608 (LINC01107)] were included in the final model of the methylation risk score for LR versus HR. These methylation risk score models of low resilience demonstrated satisfactory discrimination by logistic regression and support vector machine, with an AUC of 0.81 and 0.93, accuracy of 72.3% and 87.1%, sensitivity of 75%, and 87.5%, and specificity of 70% and 80%. Our findings suggest that methylation signatures can be utilized to identify individuals with LR and establish risk score models that may contribute to the field of psychology.

RNASE6 is a novel modifier of APOE-ε4 effects on cognition

Apolipoprotein E4 (APOE-ε4), the strongest common genetic risk factor for Alzheimer's disease (AD), contributes to worse cognition in older adults. However, many APOE-ε4 carriers remain cognitively normal throughout life, suggesting that neuroprotective factors may be present in these individuals. In this study, we leverage whole-blood RNA sequencing (RNAseq) from 324 older adults to identify genetic modifiers of APOE-ε4 effects on cognition. Expression of RNASE6 interacted with APOE-ε4 status (p = 4.35 × 10-8) whereby higher RNASE6 expression was associated with worse memory at baseline among APOE-ε4 carriers. This interaction was replicated using RNAseq data from the prefrontal cortex in an independent dataset (N = 535; p = 0.002), suggesting the peripheral effect of RNASE6 is also present in brain tissue. RNASE6 encodes an antimicrobial peptide involved in innate immune response and has been previously observed in a gene co-expression network module with other AD-related inflammatory genes, including TREM2 and MS4A. Together, these data implicate neuroinflammation in cognitive decline, and suggest that innate immune signaling may be detectable in blood and confer differential susceptibility to AD depending on APOE-ε4.

Role of PDE10A in vascular smooth muscle cell hyperplasia and pathological vascular remodelling

AIMS

Intimal hyperplasia is a common feature of vascular remodelling disorders. Accumulation of synthetic smooth muscle cell (SMC)-like cells is the main underlying cause. Current therapeutic approaches including drug-eluting stents are not perfect due to the toxicity on endothelial cells and novel therapeutic strategies are needed. Our preliminary screening for dysregulated cyclic nucleotide phosphodiesterases (PDEs) in growing SMCs revealed the alteration of PDE10A expression. Herein, we investigated the function of PDE10A in SMC proliferation and intimal hyperplasia both in vitro and in vivo.

METHODS AND RESULTS

RT-qPCR, immunoblot, and in situ proximity ligation assay were performed to determine PDE10A expression in synthetic SMCs and injured vessels. We found that PDE10A mRNA and/or protein levels are up-regulated in cultured SMCs upon growth stimulation, as well as in intimal cells in injured mouse femoral arteries. To determine the cellular functions of PDE10A, we focused on its role in SMC proliferation. The anti-mitogenic effects of PDE10A on SMCs were evaluated via cell counting, BrdU incorporation, and flow cytometry. We found that PDE10A deficiency or inhibition arrested the SMC cell cycle at G1-phase with a reduction of cyclin D1. The anti-mitotic effect of PDE10A inhibition was dependent on cGMP-dependent protein kinase Iα (PKGIα), involving C-natriuretic peptide (CNP) and particulate guanylate cyclase natriuretic peptide receptor 2 (NPR2). In addition, the effects of genetic depletion and pharmacological inhibition of PDE10A on neointimal formation were examined in a mouse model of femoral artery wire injury. Both PDE10A knockout and inhibition decreased injury-induced intimal thickening in femoral arteries by at least 50%. Moreover, PDE10A inhibition decreased ex vivo remodelling of cultured human saphenous vein segments.

CONCLUSIONS

Our findings indicate that PDE10A contributes to SMC proliferation and intimal hyperplasia at least partially via antagonizing CNP/NPR2/cGMP/PKG1α signalling and suggest that PDE10A may be a novel drug target for treating vascular occlusive disease.

Polygenic resilience scores capture protective genetic effects for Alzheimer's disease

Polygenic risk scores (PRSs) can boost risk prediction in late-onset Alzheimer's disease (LOAD) beyond apolipoprotein E (APOE) but have not been leveraged to identify genetic resilience factors. Here, we sought to identify resilience-conferring common genetic variants in (1) unaffected individuals having high PRSs for LOAD, and (2) unaffected APOE-ε4 carriers also having high PRSs for LOAD. We used genome-wide association study (GWAS) to contrast "resilient" unaffected individuals at the highest genetic risk for LOAD with LOAD cases at comparable risk. From GWAS results, we constructed polygenic resilience scores to aggregate the addictive contributions of risk-orthogonal common variants that promote resilience to LOAD. Replication of resilience scores was undertaken in eight independent studies. We successfully replicated two polygenic resilience scores that reduce genetic risk penetrance for LOAD. We also showed that polygenic resilience scores positively correlate with polygenic risk scores in unaffected individuals, perhaps aiding in staving off disease. Our findings align with the hypothesis that a combination of risk-independent common variants mediates resilience to LOAD by moderating genetic disease risk.

Genetic Variants Associated With Resilience in Human and Animal Studies

Resilience is broadly defined as the ability to maintain or regain functioning in the face of adversity and is influenced by both environmental and genetic factors. The identification of specific genetic factors and their biological pathways underpinning resilient functioning can help in the identification of common key factors, but heterogeneities in the operationalisation of resilience have hampered advances. We conducted a systematic review of genetic variants associated with resilience to enable the identification of general resilience mechanisms. We adopted broad inclusion criteria for the definition of resilience to capture both human and animal model studies, which use a wide range of resilience definitions and measure very different outcomes. Analyzing 158 studies, we found 71 candidate genes associated with resilience. OPRM1 (Opioid receptor mu 1), NPY (neuropeptide Y), CACNA1C (calcium voltage-gated channel subunit alpha1 C), DCC (deleted in colorectal carcinoma), and FKBP5 (FKBP prolyl isomerase 5) had both animal and human variants associated with resilience, supporting the idea of shared biological pathways. Further, for OPRM1, OXTR (oxytocin receptor), CRHR1 (corticotropin-releasing hormone receptor 1), COMT (catechol-O-methyltransferase), BDNF (brain-derived neurotrophic factor), APOE (apolipoprotein E), and SLC6A4 (solute carrier family 6 member 4), the same allele was associated with resilience across divergent resilience definitions, which suggests these genes may therefore provide a starting point for further research examining commonality in resilience pathways.

Exploring common genetic contributors to neuroprotection from amyloid pathology

Preclinical Alzheimer's disease describes some individuals who harbour Alzheimer's pathologies but are asymptomatic. For this study, we hypothesized that genetic variation may help protect some individuals from Alzheimer's-related neurodegeneration. We therefore conducted a genome-wide association study using 5 891 064 common variants to assess whether genetic variation modifies the association between baseline beta-amyloid, as measured by both cerebrospinal fluid and positron emission tomography, and neurodegeneration defined using MRI measures of hippocampal volume. We combined and jointly analysed genotype, biomarker and neuroimaging data from non-Hispanic white individuals who were enrolled in four longitudinal ageing studies (n = 1065). Using regression models, we examined the interaction between common genetic variants (Minor Allele Frequency >0.01), including APOE-ɛ4 and APOE-ɛ2, and baseline cerebrospinal levels of amyloid (CSF Aβ42) on baseline hippocampal volume and the longitudinal rate of hippocampal atrophy. For targeted replication of top findings, we analysed an independent dataset (n = 808) where amyloid burden was assessed by Pittsburgh Compound B ([11C]-PiB) positron emission tomography. In this study, we found that APOE-ɛ4 modified the association between baseline CSF Aβ42 and hippocampal volume such that APOE-ɛ4 carriers showed more rapid atrophy, particularly in the presence of enhanced amyloidosis. We also identified a novel locus on chromosome 3 that interacted with baseline CSF Aβ42. Minor allele carriers of rs62263260, an expression quantitative trait locus for the SEMA5B gene (P = 1.46 × 10-8; 3:122675327) had more rapid neurodegeneration when amyloid burden was high and slower neurodegeneration when amyloid was low. The rs62263260 × amyloid interaction on longitudinal change in hippocampal volume was replicated in an independent dataset (P = 0.0112) where amyloid burden was assessed by positron emission tomography. In addition to supporting the established interaction between APOE and amyloid on neurodegeneration, our study identifies a novel locus that modifies the association between beta-amyloid and hippocampal atrophy. Annotation results may implicate SEMA5B, a gene involved in synaptic pruning and axonal guidance, as a high-quality candidate for functional confirmation and future mechanistic analysis.

A Review of Oxidative Stress Products and Related Genes in Early Alzheimer's Disease

Oxidative stress is associated with the progression of Alzheimer’s disease (AD). Reactive oxygen species can modify lipids, DNA, RNA, and proteins in the brain. The products of their peroxidation and oxidation are readily detectable at incipient stages of disease. Based on these oxidation products, various biomarker-based strategies have been developed to identify oxidative stress levels in AD. Known oxidative stress-related biomarkers include lipid peroxidation products F2-isoprostanes, as well as malondialdehyde and 4-hydroxynonenal which both conjugate to specific amino acids to modify proteins, and DNA or RNA oxidation products 8-hydroxy-2’-deoxyguanosine (8-OHdG) and 8-hydroxyguanosine (8-OHG), respectively. The inducible enzyme heme oxygenase type 1 (HO-1) is found to be upregulated in response to oxidative stress-related events in the AD brain. While these global biomarkers for oxidative stress are associated with early-stage AD, they generally poorly differentiate from other neurodegenerative disorders that also coincide with oxidative stress. Redox proteomics approaches provided specificity of oxidative stress-associated biomarkers to AD pathology by the identification of oxidatively damaged pathology-specific proteins. In this review, we discuss the potential combined diagnostic value of these reported biomarkers in the context of AD and discuss eight oxidative stress-related mRNA biomarkers in AD that we newly identified using a transcriptomics approach. We review these genes in the context of their reported involvement in oxidative stress regulation and specificity for AD. Further research is warranted to establish the protein levels and their functionalities as well as the molecular mechanisms by which these potential biomarkers are involved in regulation of oxidative stress levels and their potential for determination of oxidative stress and disease status of AD patients.

Multivariate genome wide association and network analysis of subcortical imaging phenotypes in Alzheimer's disease

BACKGROUND

Genome-wide association studies (GWAS) have identified many individual genes associated with brain imaging quantitative traits (QTs) in Alzheimer's disease (AD). However single marker level association discovery may not be able to address the underlying biological interactions with disease mechanism.

RESULTS

In this paper, we used the MGAS (Multivariate Gene-based Association test by extended Simes procedure) tool to perform multivariate GWAS on eight AD-relevant subcortical imaging measures. We conducted multiple iPINBPA (integrative Protein-Interaction-Network-Based Pathway Analysis) network analyses on MGAS findings using protein-protein interaction (PPI) data, and identified five Consensus Modules (CMs) from the PPI network. Functional annotation and network analysis were performed on the identified CMs. The MGAS yielded significant hits within APOE, TOMM40 and APOC1 genes, which were known AD risk factors, as well as a few new genes such as LAMA1, XYLB, HSD17B7P2, and NPEPL1. The identified five CMs were enriched by biological processes related to disorders such as Alzheimer's disease, Legionellosis, Pertussis, and Serotonergic synapse.

CONCLUSIONS

The statistical power of coupling MGAS with iPINBPA was higher than traditional GWAS method, and yielded new findings that were missed by GWAS. This study provides novel insights into the molecular mechanism of Alzheimer's Disease and will be of value to novel gene discovery and functional genomic studies.

Identifying Mechanisms of Normal Cognitive Aging Using a Novel Mouse Genetic Reference Panel

Developing strategies to maintain cognitive health is critical to quality of life during aging. The basis of healthy cognitive aging is poorly understood; thus, it is difficult to predict who will have normal cognition later in life. Individuals may have higher baseline functioning (cognitive reserve) and others may maintain or even improve with age (cognitive resilience). Understanding the mechanisms underlying cognitive reserve and resilience may hold the key to new therapeutic strategies for maintaining cognitive health. However, reserve and resilience have been inconsistently defined in human studies. Additionally, our understanding of the molecular and cellular bases of these phenomena is poor, compounded by a lack of longitudinal molecular and cognitive data that fully capture the dynamic trajectories of cognitive aging. Here, we used a genetically diverse mouse population (B6-BXDs) to characterize individual differences in cognitive abilities in adulthood and investigate evidence of cognitive reserve and/or resilience in middle-aged mice. We tested cognitive function at two ages (6 months and 14 months) using y-maze and contextual fear conditioning. We observed heritable variation in performance on these traits (h 2 RIx̄ = 0.51-0.74), suggesting moderate to strong genetic control depending on the cognitive domain. Due to the polygenetic nature of cognitive function, we did not find QTLs significantly associated with y-maze, contextual fear acquisition (CFA) or memory, or decline in cognitive function at the genome-wide level. To more precisely interrogate the molecular regulation of variation in these traits, we employed RNA-seq and identified gene networks related to transcription/translation, cellular metabolism, and neuronal function that were associated with working memory, contextual fear memory, and cognitive decline. Using this method, we nominate the Trio gene as a modulator of working memory ability. Finally, we propose a conceptual framework for identifying strains exhibiting cognitive reserve and/or resilience to assess whether these traits can be observed in middle-aged B6-BXDs. Though we found that earlier cognitive reserve evident early in life protects against cognitive impairment later in life, cognitive performance and age-related decline fell along a continuum, with no clear genotypes emerging as exemplars of exceptional reserve or resilience - leading to recommendations for future use of aging mouse populations to understand the nature of cognitive reserve and resilience.

Cognitive Resilience to Alzheimer's Disease Pathology in the Human Brain

BACKGROUND

Past research has focused on risk factors for developing dementia, with increasing recognition of "resilient" people who live to old age with intact cognitive function despite pathological features of Alzheimer's disease (AD).

OBJECTIVE

To evaluate demographic factors, mid-life characteristics, and non-AD neuropathology findings that may be associated with cognitive resilience to AD pathology.

METHODS

We analyzed data from 276 autopsy cases with intermediate or high levels of AD pathology from the Adult Changes in Thought study. We defined cognitive resilience as having Cognitive Abilities Screening Instrument scores ≥86 within two years of death and no clinical dementia diagnosis; non-resilient people had dementia diagnoses from AD or other causes before death. We compared mid-life characteristics, demographics, and additional neuropathology findings between resilient and non-resilient people. We used multivariable logistic regression to estimate odds ratios (ORs) with 95% confidence intervals (CIs) for being resilient compared to not being resilient adjusting for demographic and neuropathology factors.

RESULTS

We classified 68 (25%) people as resilient and 208 (75%) as not resilient. A greater proportion of resilient people had a college degree (50%) compared with non-resilient (32%, p = 0.01). The odds of being resilient were significantly increased among people with a college education (OR = 2.01, 95% CI = 1.01-3.99) and significantly reduced among people with additional non-AD neuropathology findings such as hippocampal sclerosis (OR = 0.28, 95% CI = 0.09-0.89) and microinfarcts (OR = 0.34, 95% CI = 0.15-0.78).

CONCLUSION

Increased education and absence of non-AD pathology may be independently associated with cognitive resilience, highlighting the importance of evaluating co-morbid factors in future research on mechanisms of cognitive resilience.

A telescope GWAS analysis strategy, based on SNPs-genes-pathways ensamble and on multivariate algorithms, to characterize late onset Alzheimer's disease

Genome–wide association studies (GWAS) have revealed a plethora of putative susceptibility genes for Alzheimer’s disease (AD), with the sole exception of APOE gene unequivocally validated in independent study. Considering that the etiology of complex diseases like AD could depend on functional multiple genes interaction network, here we proposed an alternative GWAS analysis strategy based on (i) multivariate methods and on a (ii) telescope approach, in order to guarantee the identification of correlated variables, and reveal their connections at three biological connected levels. Specifically as multivariate methods, we employed two machine learning algorithms and a genetic association test and we considered SNPs, Genes and Pathways features in the analysis of two public GWAS dataset (ADNI-1 and ADNI-2). For each dataset and for each feature we addressed two binary classifications tasks: cases vs. controls and the low vs. high risk of developing AD considering the allelic status of APOEe4. This complex strategy allowed the identification of SNPs, genes and pathways lists statistically robust and meaningful from the biological viewpoint. Among the results, we confirm the involvement of TOMM40 gene in AD and we propose GRM7 as a novel gene significantly associated with AD.

Parental warmth interacts with several genes to affect executive function components: a genome-wide environment interaction study

Background

Executive function (EF) is vital to human beings. It has been linked to many genes and family environmental factors in separate studies, but few studies have examined the potential interactions between gene(s) and environmental factor(s). The current study explored the whole genome to identify SNPs, genes, and pathways that interacted with parental warmth (PW) on EF.

Results

Nine EF tasks were used to measure its three components (common EF, updating, shifting) based on the model proposed by Miyake et al. (2000). We found that rs111605473, LAMP5, SLC4A7, and LRRK1 interacted significantly with PW to affect the updating component of EF, and the GSE43955 pathway interacted significantly with PW to affect the common EF component.

Conclusions

The current study is the first to identify genes that interacted with PW to affect EF. Further studies are needed to reveal the underlying mechanism.

Recent Advances in the Systems Biology of Aging

SIGNIFICANCE

Reductionist studies have contributed greatly to our understanding of the basic biology of aging in recent years but we still do not understand fundamental mechanisms for many identified drugs and pathways. Use of systems approaches will help us move forward in our understanding of aging. Recent Advances: Recent work described here has illustrated the power of systems biology to inform our understanding of aging through the study of (i) diet restriction, (ii) neurodegenerative disease, and (iii) biomarkers of aging.

CRITICAL ISSUES

Although we do not understand all of the individual genes and pathways that affect aging, as we continue to uncover more of them, we have now also begun to synthesize existing data using systems-level approaches, often to great effect. The three examples noted here all benefit from computational approaches that were unknown a few years ago, and from biological insights gleaned from multiple model systems, from aging laboratories as well as many other areas of biology.

FUTURE DIRECTIONS

Many new technologies, such as single-cell sequencing, advances in epigenetics beyond the methylome (specifically, assay for transposase-accessible chromatin with high throughput sequencing ), and multiomic network studies, will increase the reach of systems biologists. This suggests that approaches similar to those described here will continue to lead to striking findings, and to interventions that may allow us to delay some of the many age-associated diseases in humans; perhaps sooner that we expect. Antioxid. Redox Signal. 29, 973-984.

A genome-wide association study of cognitive function in Chinese adult twins

Multiple loci or genes have been identified using genome-wide association studies mainly in western countries but with inconsistent results. No similar studies have been conducted in the world's largest and rapidly aging Chinese population. The paper aimed to identify the specific genetic variants associated with cognitive function in middle and old-aged Chinese dizygotic twins (DZ). Cognitive function was measured on 139 pairs of DZ by Montreal Cognitive Assessment. The subjects were genotyped at 1048575 SNP positions. Regression-based mixed-effect kinship model of GWAS was conducted to test the SNPs. Gene-based analysis was performed on VEGAS2. The statistically significant genes were then subject to gene set enrichment analysis to further identify the specific biological pathways associated with cognitive function. No SNPs reached genome-wide significance although there were 13 SNPs of suggestive significance (P < 10^-5). Gene-based analysis found 823 significant genes topped by TNRC18P1 (P = 1.00 × 10^-6), FGFR1OP2 (P = 6.00 × 10^-6), and AKR1D1 (P = 2.30 × 10^-5). Enrichment analysis identified 46 biological pathways, mainly involving in signaling transmission, metabolic process and Alzheimer's disease. Analysis of SNPs involved in the regulatory motif detected cell-type specific enhancers involving aorta and colon smooth muscle both have been reported to implicate in cognition. We conclude that genetic variations are significantly involved in functional genes, biological pathways and the regulatory domain that mediate cognitive performances.

Genome-wide association analysis identifies a GLUL haplotype for familial hepatitis B virus-related hepatocellular carcinoma

BACKGROUND

A family history of liver cancer increases the risk of developing hepatocellular carcinoma (HCC) by 2-fold to 10-fold among patients with chronic hepatitis B virus (HBV). Previous genome-wide association studies have identified many possible susceptible loci associated with sporadic HBV-related HCC. However, despite family history being a well-known risk factor for HBV-related HCC, to the authors' knowledge its genetic mechanisms and associating loci remain largely unknown or unexplored, most likely due to the relative rarity of familial HCC and the difficulty of sample collection.

METHODS

The authors conducted a genome-wide association study with 139 male cases with familial HBV-related HCC and 139 non-HCC male controls with chronic HBV. The results were corroborated further with an independent cohort of 101 patients with familial HBV-related HCC and comparison with both the 1000 Genomes Project and the Taiwan Biobank.

RESULTS

A total of 51 risk single-nucleotide polymorphisms (P≤1E-04) were identified in the association analyses, which included 2 clusters of associated single-nucleotide polymorphisms and haplotypes at 1q25.3 (glutamate-ammonia ligase [GLUL]/transmembrane epididymal protein 1 [TEDDM1]/long intergenic non-protein-coding RNA 272 [LINC00272]/regulator of G-protein signaling-like 1 [RGSL1]) and 17q11.2 (solute carrier family 13 member 2 [SLC13A2]/forkhead box N1 [FOXN1]). Both the GLUL and SLC13A2/FOXN1 haplotypes have large effect sizes and were found to be different from those found from genome-wide association studies of sporadic HCCs.

CONCLUSIONS

To the authors' knowledge, the current study is the first genome-wide association study to identify genetic factors for familial HBV-related HCC. The results identified 2 large effect susceptible haplotypes located at GLUL and SLC13A2/FOXN1. The current study findings also suggest different genetic susceptibility between familial and sporadic HBV-related HCC. Cancer 2017;123:3966-76. © 2017 American Cancer Society.

The Alzheimer's Disease Neuroimaging Initiative 3: Continued innovation for clinical trial improvement

INTRODUCTION

The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI-3, which began on August 1, 2016, is a 5-year renewal of the current ADNI-2 study.

METHODS

ADNI-3 will follow current and additional subjects with normal cognition, mild cognitive impairment, and AD using innovative technologies such as tau imaging, magnetic resonance imaging sequences for connectivity analyses, and a highly automated immunoassay platform and mass spectroscopy approach for cerebrospinal fluid biomarker analysis. A Systems Biology/pathway approach will be used to identify genetic factors for subject selection/enrichment. Amyloid positron emission tomography scanning will be standardized using the Centiloid method. The Brain Health Registry will help recruit subjects and monitor subject cognition.

RESULTS

Multimodal analyses will provide insight into AD pathophysiology and disease progression.

DISCUSSION

ADNI-3 will aim to inform AD treatment trials and facilitate development of AD disease-modifying treatments.

Recent publications from the Alzheimer's Disease Neuroimaging Initiative: Reviewing progress toward improved AD clinical trials

INTRODUCTION

The Alzheimer's Disease Neuroimaging Initiative (ADNI) has continued development and standardization of methodologies for biomarkers and has provided an increased depth and breadth of data available to qualified researchers. This review summarizes the over 400 publications using ADNI data during 2014 and 2015.

METHODS

We used standard searches to find publications using ADNI data.

RESULTS

(1) Structural and functional changes, including subtle changes to hippocampal shape and texture, atrophy in areas outside of hippocampus, and disruption to functional networks, are detectable in presymptomatic subjects before hippocampal atrophy; (2) In subjects with abnormal β-amyloid deposition (Aβ+), biomarkers become abnormal in the order predicted by the amyloid cascade hypothesis; (3) Cognitive decline is more closely linked to tau than Aβ deposition; (4) Cerebrovascular risk factors may interact with Aβ to increase white-matter (WM) abnormalities which may accelerate Alzheimer's disease (AD) progression in conjunction with tau abnormalities; (5) Different patterns of atrophy are associated with impairment of memory and executive function and may underlie psychiatric symptoms; (6) Structural, functional, and metabolic network connectivities are disrupted as AD progresses. Models of prion-like spreading of Aβ pathology along WM tracts predict known patterns of cortical Aβ deposition and declines in glucose metabolism; (7) New AD risk and protective gene loci have been identified using biologically informed approaches; (8) Cognitively normal and mild cognitive impairment (MCI) subjects are heterogeneous and include groups typified not only by "classic" AD pathology but also by normal biomarkers, accelerated decline, and suspected non-Alzheimer's pathology; (9) Selection of subjects at risk of imminent decline on the basis of one or more pathologies improves the power of clinical trials; (10) Sensitivity of cognitive outcome measures to early changes in cognition has been improved and surrogate outcome measures using longitudinal structural magnetic resonance imaging may further reduce clinical trial cost and duration; (11) Advances in machine learning techniques such as neural networks have improved diagnostic and prognostic accuracy especially in challenges involving MCI subjects; and (12) Network connectivity measures and genetic variants show promise in multimodal classification and some classifiers using single modalities are rivaling multimodal classifiers.

DISCUSSION

Taken together, these studies fundamentally deepen our understanding of AD progression and its underlying genetic basis, which in turn informs and improves clinical trial design.

Identification of EGFLAM, SPATC1L and RNASE13 as novel susceptibility loci for aortic aneurysm in Japanese individuals by exome-wide association studies

We performed an exome-wide association study (EWAS) to identify genetic variants - in particular, low‑frequency or rare variants with a moderate to large effect size - that confer susceptibility to aortic aneurysm with 8,782 Japanese subjects (456 patients with aortic aneurysm, 8,326 control individuals) and with the use of Illumina HumanExome-12 DNA Analysis BeadChip or Infinium Exome-24 BeadChip arrays. The correlation of allele frequencies for 41,432 single nucleotide polymorphisms (SNPs) that passed quality control to aortic aneurysm was examined with Fisher's exact test. Based on Bonferroni's correction, a P-value of <1.21x10-6 was considered statistically significant. The EWAS revealed 59 SNPs that were significantly associated with aortic aneurysm. None of these SNPs was significantly (P<2.12x10-4) associated with aortic aneurysm by multivariable logistic regression analysis with adjustment for age, gender and hypertension, although 8 SNPs were related (P<0.05) to this condition. Examination of the correlation of these latter 8 SNPs to true or dissecting aortic aneurysm separately showed that rs1465567 [T/C (W229R)] of the EGF-like, fibronectin type III, and laminin G domains gene (EGFLAM) (dominant model; P=0.0014; odds ratio, 1.63) was significantly (P<0.0016) associated with true aortic aneurysm. We next performed EWASs for true or dissecting aortic aneurysm separately and found that 45 and 19 SNPs were significantly associated with these conditions, respectively. Multivariable logistic regression analysis with adjustment for covariates revealed that rs113710653 [C/T (E231K)] of the spermatogenesis- and centriole associated 1-like gene (SPATC1L) (dominant model; P=0.0002; odds ratio, 5.32) and rs143881017 [C/T (R140H)] of the ribonuclease A family member 13 gene (RNASE13) (dominant model; P=0.0006; odds ratio, 5.77) were significantly (P<2.78x10-4 or P<6.58x10-4, respectively) associated with true or dissecting aortic aneurysm, respectively. EGFLAM and SPATC1L may thus be susceptibility loci for true aortic aneurysm and RNASE13 may be such a locus for dissecting aneurysm in Japanese individuals.

Searching for new loci and candidate genes for economically important traits through gene-based association analysis of Simmental cattle

Single-marker genome-wide association study (GWAS) is a convenient strategy of genetic analysis that has been successful in detecting the association of a number of single-nucleotide polymorphisms (SNPs) with quantitative traits. However, analysis of individual SNPs can only account for a small proportion of genetic variation and offers only limited knowledge of complex traits. This inadequacy may be overcome by employing a gene-based GWAS analytic approach, which can be considered complementary to the single-SNP association analysis. Here we performed an initial single-SNP GWAS for bone weight (BW) and meat pH value with a total of 770,000 SNPs in 1141 Simmental cattle. Additionally, 21836 cattle genes collected from the Ensembl Genes 83 database were analyzed to find supplementary evidence to support the importance of gene-based association study. Results of the single SNP-based association study showed that there were 11 SNPs significantly associated with bone weight (BW) and two SNPs associated with meat pH value. Interestingly, all of these SNPs were located in genes detected by the gene-based association study.

Powerful and Adaptive Testing for Multi-trait and Multi-SNP Associations with GWAS and Sequencing Data

Testing for genetic association with multiple traits has become increasingly important, not only because of its potential to boost statistical power, but also for its direct relevance to applications. For example, there is accumulating evidence showing that some complex neurodegenerative and psychiatric diseases like Alzheimer's disease are due to disrupted brain networks, for which it would be natural to identify genetic variants associated with a disrupted brain network, represented as a set of multiple traits, one for each of multiple brain regions of interest. In spite of its promise, testing for multivariate trait associations is challenging: if not appropriately used, its power can be much lower than testing on each univariate trait separately (with a proper control for multiple testing). Furthermore, differing from most existing methods for single-SNP-multiple-trait associations, we consider SNP set-based association testing to decipher complicated joint effects of multiple SNPs on multiple traits. Because the power of a test critically depends on several unknown factors such as the proportions of associated SNPs and of traits, we propose a highly adaptive test at both the SNP and trait levels, giving higher weights to those likely associated SNPs and traits, to yield high power across a wide spectrum of situations. We illuminate relationships among the proposed and some existing tests, showing that the proposed test covers several existing tests as special cases. We compare the performance of the new test with that of several existing tests, using both simulated and real data. The methods were applied to structural magnetic resonance imaging data drawn from the Alzheimer's Disease Neuroimaging Initiative to identify genes associated with gray matter atrophy in the human brain default mode network (DMN). For genome-wide association studies (GWAS), genes AMOTL1 on chromosome 11 and APOE on chromosome 19 were discovered by the new test to be significantly associated with the DMN. Notably, gene AMOTL1 was not detected by single SNP-based analyses. To our knowledge, AMOTL1 has not been highlighted in other Alzheimer's disease studies before, although it was indicated to be related to cognitive impairment. The proposed method is also applicable to rare variants in sequencing data and can be extended to pathway analysis.

Applying Novel Methods for Assessing Individual- and Neighborhood-Level Social and Psychosocial Environment Interactions with Genetic Factors in the Prediction of Depressive Symptoms in the Multi-Ethnic Study of Atherosclerosis

Complex illnesses, like depression, are thought to arise from the interplay between psychosocial stressors and genetic predispositions. Approaches that take into account both personal and neighborhood factors and that consider gene regions as well as individual SNPs may be necessary to capture these interactions across race and ethnic groups. We used novel gene-region based analysis methods [Sequence Kernel Association Test (SKAT) and meta-analysis (MetaSKAT), gene-environment set association test (GESAT)], as well as traditional linear models to identify gene region and SNP × psychosocial factor interactions at the individual- and neighborhood-level, across multiple race/ethnicities. Multiple regions identified in SKAT analyses showed evidence of a significant gene-region association with averaged depressive symptom scores across race/ethnicity (MetaSKAT p values <0.001). One region × neighborhood-environment interaction was significantly associated with averaged depressive symptom score across race/ethnicity after multiple testing correction (chr 18:21454070-21494070, Fisher's combined p value = 0.001). The examination of gene regions jointly with environmental factors measured at multiple levels (individuals and their contexts) may shed light on the etiology of depressive illness across race/ethnicities.

Genetic studies of quantitative MCI and AD phenotypes in ADNI: Progress, opportunities, and plans

INTRODUCTION

Genetic data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) have been crucial in advancing the understanding of Alzheimer's disease (AD) pathophysiology. Here, we provide an update on sample collection, scientific progress and opportunities, conceptual issues, and future plans.

METHODS

Lymphoblastoid cell lines and DNA and RNA samples from blood have been collected and banked, and data and biosamples have been widely disseminated. To date, APOE genotyping, genome-wide association study (GWAS), and whole exome and whole genome sequencing data have been obtained and disseminated.

RESULTS

ADNI genetic data have been downloaded thousands of times, and >300 publications have resulted, including reports of large-scale GWAS by consortia to which ADNI contributed. Many of the first applications of quantitative endophenotype association studies used ADNI data, including some of the earliest GWAS and pathway-based studies of biospecimen and imaging biomarkers, as well as memory and other clinical/cognitive variables. Other contributions include some of the first whole exome and whole genome sequencing data sets and reports in healthy controls, mild cognitive impairment, and AD.

DISCUSSION

Numerous genetic susceptibility and protective markers for AD and disease biomarkers have been identified and replicated using ADNI data and have heavily implicated immune, mitochondrial, cell cycle/fate, and other biological processes. Early sequencing studies suggest that rare and structural variants are likely to account for significant additional phenotypic variation. Longitudinal analyses of transcriptomic, proteomic, metabolomic, and epigenomic changes will also further elucidate dynamic processes underlying preclinical and prodromal stages of disease. Integration of this unique collection of multiomics data within a systems biology framework will help to separate truly informative markers of early disease mechanisms and potential novel therapeutic targets from the vast background of less relevant biological processes. Fortunately, a broad swath of the scientific community has accepted this grand challenge.

Integrative Bayesian variable selection with gene-based informative priors for genome-wide association studies

Background

Genome-wide Association Studies (GWAS) are typically designed to identify phenotype-associated single nucleotide polymorphisms (SNPs) individually using univariate analysis methods. Though providing valuable insights into genetic risks of common diseases, the genetic variants identified by GWAS generally account for only a small proportion of the total heritability for complex diseases. To solve this “missing heritability” problem, we implemented a strategy called integrative Bayesian Variable Selection (iBVS), which is based on a hierarchical model that incorporates an informative prior by considering the gene interrelationship as a network. It was applied here to both simulated and real data sets.

Results

Simulation studies indicated that the iBVS method was advantageous in its performance with highest AUC in both variable selection and outcome prediction, when compared to Stepwise and LASSO based strategies. In an analysis of a leprosy case–control study, iBVS selected 94 SNPs as predictors, while LASSO selected 100 SNPs. The Stepwise regression yielded a more parsimonious model with only 3 SNPs. The prediction results demonstrated that the iBVS method had comparable performance with that of LASSO, but better than Stepwise strategies.

Conclusions

The proposed iBVS strategy is a novel and valid method for Genome-wide Association Studies, with the additional advantage in that it produces more interpretable posterior probabilities for each variable unlike LASSO and other penalized regression methods.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-014-0130-7) contains supplementary material, which is available to authorized users.

Genetic modification of the relationship between phosphorylated tau and neurodegeneration

BACKGROUND

A subset of individuals present at autopsy with the pathologic features of Alzheimer's 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.

METHODS

We used data from 700 subjects enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI). A genome-wide association study approach was used to identify PTau × single nucleotide polymorphism (SNP) interactions. Variance explained by these interactions was quantified using hierarchical linear regression.

RESULTS

Five SNP × PTau interactions passed a Bonferroni correction, one of which (rs4728029, POT1, 2.6% of variance) was consistent across ADNI-1 and ADNI-2/GO subjects. This interaction also showed a trend-level association with memory performance and levels of interleukin-6 receptor.

CONCLUSIONS

Our results suggest that rs4728029 modifies the relationship between PTau and both ventricular dilation and cognition, perhaps through an altered neuroinflammatory response.

Involvement of endocytosis and alternative splicing in the formation of the pathological process in the early stages of Parkinson's disease

Parkinson's disease (PD) is the one of most widespread neurodegenerative pathologies. Because of the impossibility of studying the endogenous processes that occur in the brain of patients with PD in the presymptomatic stage, the mechanisms that trigger the disease remain unknown. Thus, the identification of the processes that play an important role in the early stages of the disease in these patients is extremely difficult. In this context, we performed a whole-transcriptome analysis of the peripheral blood of untreated patients with stage 1 PD (Hoehn-Yahr scale). We demonstrated a significant change in the levels of transcripts included in the large groups of processes associated with the functioning of the immune system and cellular transport. Moreover, a significant change in the splicing of genes involved in cellular-transport processes was shown in our study.