Connecting the dots: potential of data integration to identify regulatory SNPs in late-onset Alzheimer's disease GWAS findings

Genetic associations vary across the spectrum of fasting serum insulin: results from the European IDEFICS/I.Family children's cohort

AIMS/HYPOTHESIS

There is increasing evidence for the existence of shared genetic predictors of metabolic traits and neurodegenerative disease. We previously observed a U-shaped association between fasting insulin in middle-aged women and dementia up to 34 years later. In the present study, we performed genome-wide association (GWA) analyses for fasting serum insulin in European children with a focus on variants associated with the tails of the insulin distribution.

METHODS

Genotyping was successful in 2825 children aged 2-14 years at the time of insulin measurement. Because insulin levels vary during childhood, GWA analyses were based on age- and sex-specific z scores. Five percentile ranks of z-insulin were selected and modelled using logistic regression, i.e. the 15th, 25th, 50th, 75th and 85th percentile ranks (P15-P85). Additive genetic models were adjusted for age, sex, BMI, survey year, survey country and principal components derived from genetic data to account for ethnic heterogeneity. Quantile regression was used to determine whether associations with variants identified by GWA analyses differed across quantiles of log-insulin.

RESULTS

A variant in the SLC28A1 gene (rs2122859) was associated with the 85th percentile rank of the insulin z score (P85, p value=3×10-8). Two variants associated with low z-insulin (P15, p value <5×10-6) were located on the RBFOX1 and SH3RF3 genes. These genes have previously been associated with both metabolic traits and dementia phenotypes. While variants associated with P50 showed stable associations across the insulin spectrum, we found that associations with variants identified through GWA analyses of P15 and P85 varied across quantiles of log-insulin.

CONCLUSIONS/INTERPRETATION

The above results support the notion of a shared genetic architecture for dementia and metabolic traits. Our approach identified genetic variants that were associated with the tails of the insulin spectrum only. Because traditional heritability estimates assume that genetic effects are constant throughout the phenotype distribution, the new findings may have implications for understanding the discrepancy in heritability estimates from GWA and family studies and for the study of U-shaped biomarker-disease associations.

Neuroimaging Genetics and Network Analysis in Alzheimer's Disease

The issue of the genetics in brain imaging phenotypes serves as a crucial link between two distinct scientific fields: neuroimaging genetics (NG). The articles included here provide solid proof that this NG link has considerable synergy. There is a suitable collection of articles that offer a wide range of viewpoints on how genetic variations affect brain structure and function. They serve as illustrations of several study approaches used in contemporary genetics and neuroscience. Genome-wide association studies and candidate-gene association are two examples of genetic techniques. Cortical gray matter structural/volumetric measures from magnetic resonance imaging (MRI) are sources of information on brain phenotypes. Together, they show how various scientific disciplines have benefited from significant technological advances, such as the single-nucleotide polymorphism array in genetics and the development of increasingly higher-resolution MRI imaging. Moreover, we discuss NG's contribution to expanding our knowledge about the heterogeneity within Alzheimer's disease as well as the benefits of different network analyses.

The chaperone Clusterin in neurodegeneration-friend or foe?

Fibrillar protein aggregates are the pathological hallmark of a group of age-dependent neurodegenerative conditions, including Alzheimer's and Parkinson's disease. Aggregates of the microtubule-associated protein Tau are observed in Alzheimer's disease and primary tauopathies. Tau pathology propagates from cell to cell in a prion-like process that is likely subject to modulation by extracellular chaperones such as Clusterin. We recently reported that Clusterin delayed Tau fibril formation but enhanced the activity of Tau oligomers to seed aggregation of endogenous Tau in a cellular model. In contrast, Clusterin inhibited the propagation of α-Synuclein aggregates associated with Parkinson's disease. These findings raise the possibility of a mechanistic link between Clusterin upregulation observed in Alzheimer's disease and the progression of Tau pathology. Here we review the diverse functions of Clusterin in the pathogenesis of neurodegenerative diseases, focusing on evidence that Clusterin may act either as a suppressor or enhancer of pathology.

Bioinformatics pipeline to guide late-onset Alzheimer's disease (LOAD) post-GWAS studies: Prioritizing transcription regulatory variants within LOAD-associated regions

INTRODUCTION

As new late-onset Alzheimer's disease (LOAD) genetic risk loci are identified and brain cell-type specific omics data becomes available, there is an unmet need for a bioinformatics framework to prioritize genes and variants for testing in single-cell molecular profiling experiments and validation using disease models and gene editing technologies. Prior work has characterized and prioritized active enhancers located in LOAD-genome-wide association study (GWAS) regions and their potential interactions with candidate genes. The current study extends this work by focusing on single nucleotide polymorphisms (SNPs) within these LOAD enhancers and their impact on altering transcription factor (TF) binding. The proposed bioinformatics pipeline progresses from SNPs located in LOAD-GWAS regions to a filtered set of candidate regulatory SNPs that have a predicted strong effect on TF binding.

METHODS

Active enhancers within LOAD-associated regions were identified and SNPs located in the enhancers were catalogued. SNPs that disrupt TF binding sites were prioritized and the respective TFs were filtered to include only those that were expressed in brain tissues relevant to LOAD. The TFs binding to the corresponding sequence was further confirmed by ChIP-seq signals. Finally, the high-priority candidate SNPs were evaluated as expression quantitative trait loci (eQTLs) in disease-relevant tissues.

RESULTS

We catalogued 61 strong enhancers in LOAD-GWAS regions encompassing 326 SNPs and 104 TF binding sites. Seventy-seven and 78 of the TFs were expressed in brain and monocytes, respectively, out of which 19 TF-binding sites showed ChIP-seq signals. Eleven SNPs were found to interrupt with TF binding out of which three SNPs were also significant eQTL.

DISCUSSION

This study provides a framework to catalogue noncoding variations in enhancers located in LOAD-GWAS loci and characterize their likelihood to perturb TF binding. The approach integrates multiple data types to characterize and prioritize SNPs for putative regulatory function using single-cell multi-omics assays and gene editing.

A machine learning approach to brain epigenetic analysis reveals kinases associated with Alzheimer's disease

Alzheimer's disease (AD) is influenced by both genetic and environmental factors; thus, brain epigenomic alterations may provide insights into AD pathogenesis. Multiple array-based Epigenome-Wide Association Studies (EWASs) have identified robust brain methylation changes in AD; however, array-based assays only test about 2% of all CpG sites in the genome. Here, we develop EWASplus, a computational method that uses a supervised machine learning strategy to extend EWAS coverage to the entire genome. Application to six AD-related traits predicts hundreds of new significant brain CpGs associated with AD, some of which are further validated experimentally. EWASplus also performs well on data collected from independent cohorts and different brain regions. Genes found near top EWASplus loci are enriched for kinases and for genes with evidence for physical interactions with known AD genes. In this work, we show that EWASplus implicates additional epigenetic loci for AD that are not found using array-based AD EWASs.

Defining functional variants associated with Alzheimer's disease in the induced immune response

Defining the mechanisms involved in the aetiology of Alzheimer’s disease from genome-wide association studies alone is challenging since Alzheimer’s disease is polygenic and most genetic variants are non-coding. Non-coding Alzheimer’s disease risk variants can influence gene expression by affecting miRNA binding and those located within enhancers and within CTCF sites may influence gene expression through alterations in chromatin states. In addition, their function can be cell-type specific. They can function specifically in microglial enhancers thus affecting gene expression in the brain. Hence, transcriptome-wide association studies have been applied to test the genetic association between disease risk and cell-/tissue-specific gene expression. Many Alzheimer’s disease-associated loci are involved in the pathways of the innate immune system. Both microglia, the primary immune cells of the brain, and monocytes which can infiltrate the brain and differentiate into activated macrophages, have roles in neuroinflammation and β‐amyloid clearance through phagocytosis. In monocytes the function of regulatory variants can be context-specific after immune stimulation. To dissect the variants associated with Alzheimer’s disease in the context of monocytes, we utilized data from naïve monocytes and following immune stimulation in vitro, in combination with genome-wide association studies of Alzheimer’s disease in transcriptome-wide association studies. Of the nine genes with statistically independent transcriptome-wide association signals, seven are located in known Alzheimer’s disease risk loci: BIN1, PTK2B, SPI1, MS4A4A, MS4A6E, APOE and PVR. The transcriptome-wide association signal for MS4A6E, PTK2B and PVR and the direction of effect replicated in an independent genome-wide association studies. Our analysis identified two novel candidate genes for Alzheimer’s disease risk, LACTB2 and PLIN2/ADRP. LACTB2 replicated in a transcriptome-wide association study using independent expression weights. LACTB2 and PLIN2/ADRP are involved in mitochondrial function and lipid metabolism, respectively. Comparison of transcriptome-wide association study results from monocytes, whole blood and brain showed that the signal for PTK2B is specific to blood and MS4A6E is specific to LPS stimulated monocytes.

The Dual Roles of Clusterin in Extracellular and Intracellular Proteostasis

Clusterin (CLU) was the first reported secreted mammalian chaperone and impacts on serious diseases associated with inappropriate extracellular protein aggregation. Many studies have described intracellular CLU in locations outside the secretory system and recent work has shown that CLU can be released into the cytosol during cell stress. In this article, we critically evaluate evidence relevant to the proposed origins of cellular CLU found outside the secretory system, and advance the hypothesis that the cytosolic release of CLU induced by stress serves to facilitate the trafficking of misfolded proteins to the proteasome and autophagy for degradation. We also propose future research directions that could help establish CLU as a unique chaperone performing critical and synergic roles in both intracellular and extracellular proteostasis.

A multiomics approach to heterogeneity in Alzheimer's disease: focused review and roadmap

Aetiological and clinical heterogeneity is increasingly recognized as a common characteristic of Alzheimer's disease and related dementias. This heterogeneity complicates diagnosis, treatment, and the design and testing of new drugs. An important line of research is discovery of multimodal biomarkers that will facilitate the targeting of subpopulations with homogeneous pathophysiological signatures. High-throughput 'omics' are unbiased data-driven techniques that probe the complex aetiology of Alzheimer's disease from multiple levels (e.g. network, cellular, and molecular) and thereby account for pathophysiological heterogeneity in clinical populations. This review focuses on data reduction analyses that identify complementary disease-relevant perturbations for three omics techniques: neuroimaging-based subtypes, metabolomics-derived metabolite panels, and genomics-related polygenic risk scores. Neuroimaging can track accrued neurodegeneration and other sources of network impairments, metabolomics provides a global small-molecule snapshot that is sensitive to ongoing pathological processes, and genomics characterizes relatively invariant genetic risk factors representing key pathways associated with Alzheimer's disease. Following this focused review, we present a roadmap for assembling these multiomics measurements into a diagnostic tool highly predictive of individual clinical trajectories, to further the goal of personalized medicine in Alzheimer's disease.

Challenges of Immune Response Diversity in the Human Population Concerning New Tuberculosis Diagnostics, Therapies, and Vaccines

Universal approaches to the prevention and treatment of human diseases fail to take into account profound immune diversity resulting from genetic variations across populations. Personalized or precision medicine takes into account individual lifestyle, environment, and biology (genetics and immune status) and is being adopted in several disease intervention strategies such as cancer and heart disease. However, its application in infectious diseases, particularly global diseases such as tuberculosis (TB), is far more complex and in a state of infancy. Here, we discuss the impact of human genetic variations on immune responses and how they relate to failures seen in current TB diagnostic, therapy, and vaccine approaches across populations. We offer our perspective on the challenges and potential for more refined approaches going forward.

Enhancer variants associated with Alzheimer's disease affect gene expression via chromatin looping

BACKGROUND

Genome-wide association studies (GWASs) have identified single-nucleotide polymorphisms (SNPs) that may be genetic factors underlying Alzheimer's disease (AD). However, how these AD-associated SNPs (AD SNPs) contribute to the pathogenesis of this disease is poorly understood because most of them are located in non-coding regions, such as introns and intergenic regions. Previous studies reported that some disease-associated SNPs affect regulatory elements including enhancers. We hypothesized that non-coding AD SNPs are located in enhancers and affect gene expression levels via chromatin loops.

METHODS

To characterize AD SNPs within non-coding regions, we extracted 406 AD SNPs with GWAS p-values of less than 1.00 × 10- 6 from the GWAS catalog database. Of these, we selected 392 SNPs within non-coding regions. Next, we checked whether those non-coding AD SNPs were located in enhancers that typically regulate gene expression levels using publicly available data for enhancers that were predicted in 127 human tissues or cell types. We sought expression quantitative trait locus (eQTL) genes affected by non-coding AD SNPs within enhancers because enhancers are regulatory elements that influence the gene expression levels. To elucidate how the non-coding AD SNPs within enhancers affect the gene expression levels, we identified chromatin-chromatin interactions by Hi-C experiments.

RESULTS

We report the following findings: (1) nearly 30% of non-coding AD SNPs are located in enhancers; (2) eQTL genes affected by non-coding AD SNPs within enhancers are associated with amyloid beta clearance, synaptic transmission, and immune responses; (3) 95% of the AD SNPs located in enhancers co-localize with their eQTL genes in topologically associating domains suggesting that regulation may occur through chromatin higher-order structures; (4) rs1476679 spatially contacts the promoters of eQTL genes via CTCF-CTCF interactions; (5) the effect of other AD SNPs such as rs7364180 is likely to be, at least in part, indirect through regulation of transcription factors that in turn regulate AD associated genes.

CONCLUSION

Our results suggest that non-coding AD SNPs may affect the function of enhancers thereby influencing the expression levels of surrounding or distant genes via chromatin loops. This result may explain how some non-coding AD SNPs contribute to AD pathogenesis.

Non-coding variability at the APOE locus contributes to the Alzheimer's risk

Alzheimer’s disease (AD) is a leading cause of mortality in the elderly. While the coding change of APOE-ε4 is a key risk factor for late-onset AD and has been believed to be the only risk factor in the APOE locus, it does not fully explain the risk effect conferred by the locus. Here, we report the identification of AD causal variants in PVRL2 and APOC1 regions in proximity to APOE and define common risk haplotypes independent of APOE-ε4 coding change. These risk haplotypes are associated with changes of AD-related endophenotypes including cognitive performance, and altered expression of APOE and its nearby genes in the human brain and blood. High-throughput genome-wide chromosome conformation capture analysis further supports the roles of these risk haplotypes in modulating chromatin states and gene expression in the brain. Our findings provide compelling evidence for additional risk factors in the APOE locus that contribute to AD pathogenesis.

Several studies show that APOE-ε4 coding variants are associated with Alzheimer’s disease (AD) risk. Here, Zhou et al. perform fine-mapping of the APOE region and find AD risk haplotypes with non-coding variants in the PVRL2 and APOC1 regions that are associated with relevant endophenotypes.

Clusterin in Alzheimer's Disease: Mechanisms, Genetics, and Lessons From Other Pathologies

Clusterin (CLU) or APOJ is a multifunctional glycoprotein that has been implicated in several physiological and pathological states, including Alzheimer's disease (AD). With a prominent extracellular chaperone function, additional roles have been discussed for clusterin, including lipid transport and immune modulation, and it is involved in pathways common to several diseases such as cell death and survival, oxidative stress, and proteotoxic stress. Although clusterin is normally a secreted protein, it has also been found intracellularly under certain stress conditions. Multiple hypotheses have been proposed regarding the origin of intracellular clusterin, including specific biogenic processes leading to alternative transcripts and protein isoforms, but these lines of research are incomplete and contradictory. Current consensus is that intracellular clusterin is most likely to have exited the secretory pathway at some point or to have re-entered the cell after secretion. Clusterin's relationship with amyloid beta (Aβ) has been of great interest to the AD field, including clusterin's apparent role in altering Aβ aggregation and/or clearance. Additionally, clusterin has been more recently identified as a mediator of Aβ toxicity, as evidenced by the neuroprotective effect of CLU knockdown and knockout in rodent and human iPSC-derived neurons. CLU is also the third most significant genetic risk factor for late onset AD and several variants have been identified in CLU. Although the exact contribution of these variants to altered AD risk is unclear, some have been linked to altered CLU expression at both mRNA and protein levels, altered cognitive and memory function, and altered brain structure. The apparent complexity of clusterin's biogenesis, the lack of clarity over the origin of the intracellular clusterin species, and the number of pathophysiological functions attributed to clusterin have all contributed to the challenge of understanding the role of clusterin in AD pathophysiology. Here, we highlight clusterin's relevance to AD by discussing the evidence linking clusterin to AD, as well as drawing parallels on how the role of clusterin in other diseases and pathways may help us understand its biological function(s) in association with AD.

Genetic Markers of Alzheimer's Disease

Alzheimer's disease is a complex and heterogeneous, severe neurodegenerative disorder and the predominant form of dementia, characterized by cognitive disturbances, behavioral and psychotic symptoms, progressive cognitive decline, disorientation, behavioral changes, and death. Genetic background of Alzheimer's disease differs between early-onset familial Alzheimer's disease, other cases of early-onset Alzheimer's disease, and late-onset Alzheimer's disease. Rare cases of early-onset familial Alzheimer's diseases are caused by high-penetrant mutations in genes coding for amyloid precursor protein, presenilin 1, and presenilin 2. Late-onset Alzheimer's disease is multifactorial and associated with many different genetic risk loci (>20), with the apolipoprotein E ε4 allele being a major genetic risk factor for late-onset Alzheimer's disease. Genetic and genomic studies offer insight into many additional genetic risk loci involved in the genetically complex nature of late-onset Alzheimer's disease. This review highlights the contributions of individual loci to the pathogenesis of Alzheimer's disease and suggests that their exact contribution is still not clear. Therefore, the use of genetic markers of Alzheimer's disease, for monitoring development, time course, treatment response, and prognosis of Alzheimer's disease, is still far away from the clinical application, because the contribution of genetic variations to the relative risk of developing Alzheimer's disease is limited. In the light of prediction and prevention of Alzheimer's disease, a novel approach could be found in the form of additive genetic risk scores, which combine additive effects of numerous susceptibility loci.

A Longitudinal Imaging Genetics Study of Neuroanatomical Asymmetry in Alzheimer's Disease

BACKGROUND

Contralateral brain structures represent a unique, within-patient reference element for disease, and asymmetries can provide a personalized measure of the accumulation of past disease processes. Neuroanatomical shape asymmetries have recently been associated with the progression of Alzheimer's disease (AD), but the biological basis of asymmetric brain changes in AD remains unknown.

METHODS

We investigated genetic influences on brain asymmetry by identifying associations between magnetic resonance imaging-derived measures of asymmetry and candidate single nucleotide polymorphisms (SNPs) that have previously been identified in genome-wide association studies for AD diagnosis and for brain subcortical volumes. For analyzing longitudinal neuroimaging data (1241 individuals, 6395 scans), we used a mixed effects model with interaction between genotype and diagnosis.

RESULTS

Significant associations between asymmetry of the amygdala, hippocampus, and putamen and SNPs in the genes BIN1, CD2AP, ZCWPW1, ABCA7, TNKS, and DLG2 were found.

CONCLUSIONS

The associations between SNPs in the genes TNKS and DLG2 and AD-related increases in shape asymmetry are of particular interest; these SNPs have previously been associated with subcortical volumes of amygdala and putamen but have not yet been associated with AD pathology. For AD candidate SNPs, we extend previous work to show that their effects on subcortical brain structures are asymmetric. This provides novel evidence about the biological underpinnings of brain asymmetry as a disease marker.

Data integration for functional annotation of regulatory single nucleotide polymorphisms associated with Alzheimer's disease susceptibility

BACKGROUND

Alzheimer's disease (AD), the most common form of dementia affects 24.3 million people worldwide. More than twenty genetic loci have been associated with AD and a significant number of genetic variants were mapped within these loci. A large proportion of genome wide significant variants lie outside the coding region. However, the plausible function of these variants is still unexplored.

OBJECTIVE

The present study aimed to unravel the regulatory role of proxy single nucleotide polymorphisms (SNPs), to determine their risk of developing AD.

METHODS

The RegulomeDB was employed to predict the regulatory role of proxy SNPs. Protein association network and functional enrichment analysis was performed using String10.5 and gene ontology, respectively.

RESULTS

A total of 451 SNPs were examined through SNAP web portal (r² ≤ 0.80) which returned 2186 proxy SNPs in linkage disequilibrium (LD) with genome wide significant SNPs for AD. Out of 2186 SNPs analyzed in RegulomeDB, 151 had the scores < 3 that indicates the high degree of their potential regulatory function. Further analysis revealed that out of these 151 SNPs, 37 were genome wide significant for AD, 17 were significantly associated with diseases other than AD, 89 were proxy SNPs (not genome wide significant) for various diseases including AD while 8 SNPs were novel proxy SNPs for AD.

CONCLUSION

These findings support the notion that the non-coding variants can be strongly associated with disease risk. Further validation through genome wide association studies will be helpful for the elucidation of their regulatory potential.

Association and interaction effects of Alzheimer's disease-associated genes and lifestyle on cognitive aging in older adults in a Taiwanese population

Genome-wide association studies and meta-analyses implicated that increased risk of developing Alzheimers diseases (AD) has been associated with the ABCA7, APOE, BIN1, CASS4, CD2AP, CD33, CELF1, CLU, CR1, DSG2, EPHA1, FERMT2, HLA-DRB1, HLA-DRB4, INPP5D, MEF2C, MS4A4A, MS4A4E, MS4A6E, NME8, PICALM, PLD3, PTK2B, RIN3, SLC24A4, SORL1, and ZCWPW1 genes. In this study, we assessed whether single nucleotide polymorphisms (SNPs) within these 27 AD-associatedgenes are linked with cognitive aging independently and/or through complex interactions in an older Taiwanese population. We also analyzed the interactions between lifestyle and these genes in influencing cognitive aging. A total of 634 Taiwanese subjects aged over 60 years from the Taiwan Biobank were analyzed. Mini-Mental State Examination (MMSE) scores were performed for all subjects to evaluate cognitive functions. Out of the 588 SNPs tested in this study, only the association between CASS4-rs911159 and cognitive aging persisted significantly (P = 2.2 × 10⁻⁵) after Bonferroni correction. Our data also showed a nominal association of cognitive aging with the SNPs in six more key AD-associated genes, including EPHA1-rs10952552, FERMT2-rs4901317, MEF2C-rs9293506, PLD3-rs11672825, RIN3-rs1885747, and SLC24A4-rs67063100 (P = 0.0018∼0.0097). Additionally, we found the interactions among CASS4-rs911159, EPHA-rs10952552, FERMT2-rs4901317, MEF2C-rs9293506, or SLC24A4-rs67063100 on cognitive aging (P = 0.004∼0.035). Moreover, our analysis suggested the interactions of SLC24A4-rs67063100 or MEF2C-rs9293506 with lifestyle such as alcohol consumption, smoking status, physical activity, or social support on cognitive aging (P = 0.008∼0.041). Our study indicates that the AD-associated genes may contribute to the risk of cognitive aging independently as well as through gene-gene and gene-lifestyle interactions.

ZCWPW1 is associated with late-onset Alzheimer's disease in Han Chinese: a replication study and meta-analyses

Recently, a large genome-wide association study (GWAS) has identified a novel variant (rs1476679) within ZCWPW1 showing strong association with late-onset Alzheimer's disease (LOAD) in Caucasian. However, the effect of rs1476679 on other populations remains unclear. In order to explore whether rs1476679 is also associated with the LOAD risk in other ethnic groups, we recruited 2350 unrelated Northern Han Chinese subjects, which include 992 LOAD patients and 1358 healthy controls. Analysis of data from these subjects suggests that the rs1476679 polymorphism is significantly associated with the LOAD (genotype P = 0.017, allele P = 0.044). The logistic regression reveals the C allele at rs1476679 is a protective factor for LOAD in the dominant model (OR = 0.779, 95%CI = 0.659–0.921, Pc = 0.009) adjusting for gender, age and APOE ε4 status. Furthermore, rs1476679 can decrease the AD risk (Dominant: OR = 0.733, 95%CI = 0.607–0.884, Pc = 0.006; Additive: OR = 0.820, 95%CI = 0.708–0.950, Pc = 0.048) in APOE ε4 non-carriers after stratification. Furthermore, meta-analysis of 82525 individuals confirmed that rs1476679 within ZCWPW1 decreased the risk of LOAD (OR = 0.91, 95%CI = 0.89–0.94). To summarize, the rs1476679 polymorphism in ZCWPW1 is associated with LOAD in Northern Han Chinese population.

Linking Alzheimer's disease and type 2 diabetes: Novel shared susceptibility genes detected by cFDR approach

BACKGROUND

Both type 2 diabetes (T2D) and Alzheimer's disease (AD) occur commonly in the aging populations and T2D has been considered as an important risk factor for AD. The heritability of both diseases is estimated to be over 50%. However, common pleiotropic single-nucleotide polymorphisms (SNPs)/loci have not been well-defined. The aim of this study is to analyze two large public accessible GWAS datasets to identify novel common genetic loci for T2D and/or AD.

METHODS AND MATERIALS

The recently developed novel conditional false discovery rate (cFDR) approach was used to analyze the summary GWAS datasets from International Genomics of Alzheimer's Project (IGAP) and Diabetes Genetics Replication And Meta-analysis (DIAGRAM) to identify novel susceptibility genes for AD and T2D.

RESULTS

We identified 78 SNPs (including 58 novel SNPs) that were associated with AD in Europeans conditional on T2D (cFDR<0.05). 66 T2D SNPs (including 40 novel SNPs) were identified by conditioning on SNPs association with AD (cFDR<0.05). A conjunction-cFDR (ccFDR) analysis detected 8 pleiotropic SNPs with a significance threshold of ccFDR<0.05 for both AD and T2D, of which 5 SNPs (rs6982393, rs4734295, rs7812465, rs10510109, rs2421016) were novel findings. Furthermore, among the 8 SNPs annotated at 6 different genes, 3 corresponding genes TP53INP1, TOMM40 and C8orf38 were related to mitochondrial dysfunction, critically involved in oxidative stress, which potentially contribute to the etiology of both AD and T2D.

CONCLUSION

Our study provided evidence for shared genetic loci between T2D and AD in European subjects by using cFDR and ccFDR analyses. These results may provide novel insight into the etiology and potential therapeutic targets of T2D and/or AD.

Functional annotation of Alzheimer's disease associated loci revealed by GWASs

Genome-wide association studies (GWASs) discovered a number of SNPs and genes associated with Alzheimer's disease (AD). However, how these SNPs and genes influence the liability to AD is not fully understood. We deployed computational approaches to explore the function and action mechanisms of AD -related SNPs and genes identified by GWASs, including the effects of 195 GWAS lead SNPs and 338 proxy SNPs on miRNAs binding and protein phosphorylation, their RegulomeDB and 3DSNP scores, and gene ontology, pathway enrichment and protein-protein interaction network of 126 AD-associated genes. Our computational analysis identified 6 lead SNPs (rs10119, rs1048699, rs148763909, rs610932, rs6857 and rs714948) and 2 proxy SNPs (rs12539172 and rs2847655) that potentially impacted the miRNA binding. Lead SNP rs2296160 and proxy SNPs rs679620 and rs2228145 were identified as PhosSNPs potentially influencing protein phosphorylation. AD-associated genes showed enrichment of “regulation of beta-amyloid formation”, “regulation of neurofibrillary tangle assembly”, “leukocyte mediated immunity” and “protein-lipid complex assembly” signaling pathway. Protein-protein interaction network and functional module analyses identified highly-interconnected “hub” genes (APOE, PICALM, BIN1, ABCA7, CD2AP, CLU, CR1, MS4A4E and MS4A6A) and bottleneck genes (APOE, TOMM40, NME8, PICALM, CD2AP, ZCWPW1, FAM180B, GAB2 and PTK2B) that created three tight subnetworks. Our results provided the targets for further experimental assessment and further insight on AD pathophysiology.

A post-GWAS analysis of predicted regulatory variants and tuberculosis susceptibility

Utilizing data from published tuberculosis (TB) genome-wide association studies (GWAS), we use a bioinformatics pipeline to detect all polymorphisms in linkage disequilibrium (LD) with variants previously implicated in TB disease susceptibility. The probability that these variants had a predicted regulatory function was estimated using RegulomeDB and Ensembl's Variant Effect Predictor. Subsequent genotyping of these 133 predicted regulatory polymorphisms was performed in 400 admixed South African TB cases and 366 healthy controls in a population-based case-control association study to fine-map the causal variant. We detected associations between tuberculosis susceptibility and six intronic polymorphisms located in MARCO, IFNGR2, ASHAS2, ACACA, NISCH and TLR10. Our post-GWAS approach demonstrates the feasibility of combining multiple TB GWAS datasets with linkage information to identify regulatory variants associated with this infectious disease.

Genetic Biomarkers on Age-Related Cognitive Decline

With ever-increasing elder populations, age-related cognitive decline, which is characterized as a gradual decline in cognitive capacity in the aging process, has turned out to be a mammoth public health concern. Since genetic information has become increasingly important to explore the biological mechanisms of cognitive decline, the search for genetic biomarkers of cognitive aging has received much attention. There is growing evidence that single-nucleotide polymorphisms (SNPs) within the ADAMTS9, BDNF, CASS4, COMT, CR1, DNMT3A, DTNBP1, REST, SRR, TOMM40, circadian clock, and Alzheimer's diseases-associated genes may contribute to susceptibility to cognitive aging. In this review, we first illustrated evidence of the genetic contribution to disease susceptibility to age-related cognitive decline in recent studies ranging from approaches of candidate genes to genome-wide association studies. We then surveyed a variety of association studies regarding age-related cognitive decline with consideration of gene-gene and gene-environment interactions. Finally, we highlighted their limitations and future directions. In light of advances in precision medicine and multi-omics technologies, future research in genomic medicine promises to lead to innovative ideas that are relevant to disease prevention and novel drugs for cognitive aging.

Proficiency of data interpretation: identification of signaling SNPs/specific loci for coronary artery disease

Database URLs

http://www.regulomedb.org/;https://www.broadinstitute.org/mpg/snap/.

Exploration and detection of potential regulatory variants in refractive error GWAS

Refractive error (RE) is a complex multifactorial disease. Genome-wide association studies (GWAS) have provided significant insight into the genetic architecture and identified plenty of robust genetic variations or single nucleotide polymorphisms (SNPs) associated with complex disease. A major current challenge is to convert those resources into causal variants and target genes. We used RegulomeDB and HaploReg to annotate regulatory information onto associated SNPs derived from the two largest RE GWAS, and additional SNPs in linkage disequilibrium (LD) with GWAS significant SNPs. Overall 868 SNPs were investigated, out of which 662 returned RegulomeDB scores of 1 to 6. It was observed that 36 out of those SNPs show strong evidence of regulatory effects with a RegulomeDB score of 1, while only four of them were GWAS significant SNPs (CD55/rs1652333, CNDP2/rs12971120, RDH5/rs3138142 and rs3138144). The results encourage us to explore those putative pathogenic variants, both GWAS significant SNPs as well as the SNPs in LD, for future discernment of functional consequence. This study offers the attractive approach for prioritizing potential functional variants by combining ENCODE data and GWAS information, and provide further insights into the pathogenesis and mechanism and ultimately therapeutics.

Functional intronic ERCC1 polymorphism from regulomeDB can predict survival in lung cancer after surgery

We searched for potential regulatory single nucleotide polymorphisms (SNPs) in excision repair cross-complementing group 1 (ERCC1) using RegulomeDB, a database integrating information from the Encyclopedia of DNA Elements (ENCODE) project, and investigated their association with survival after surgery in non-small cell lung cancer (NSCLC). Among 364 SNPs found within ERCC1 region using RegulomeDB, four top priority SNPs (rs2298881C>A, rs1049739A>G, rs10415949A>G and rs6509214G>T) were selected for this study. The four SNPs were investigated in 316 patients. A replication study was performed (n = 579). Of the four SNPs analyzed in the discovery set, rs2298881C>A and rs6509214G>T were significantly associated with survival outcomes. The association was consistently observed only for rs2298881C>A in the validation cohort. In combined analysis, rs2298881C>A was significantly associated with worse overall survival and disease-free survival (P = 0.0002 and 0.02, respectively). A decreased reporter gene expression for rs2298881 A allele was observed compared with C allele by luciferase assay (P = 0.02). ERCC1 rs2298881C>A, an intronic SNP, is the first genetic polymorphism with functional evidence of regulating its expression, and the SNP is associated with prognosis of NSCLC. Our result supports the role of RegulomeDB as a comprehensive source of prioritized candidate SNPs for genetic association studies.

Genes associated with Alzheimer's disease: an overview and current status

Alzheimer's disease (AD) is a progressive, neurodegenerative disease and the most common form of dementia in elderly people. It is an emerging public health problem that poses a huge societal burden. Linkage analysis was the first milestone in unraveling the mutations in APP, PSEN1, and PSEN2 that cause early-onset AD, followed by the discovery of apolipoprotein E-ε4 allele as the only one genetic risk factor for late-onset AD. Genome-wide association studies have revolutionized genetic research and have identified over 20 genetic loci associated with late-onset AD. Recently, next-generation sequencing technologies have enabled the identification of rare disease variants, including unmasking small mutations with intermediate risk of AD in PLD3, TREM2, UNC5C, AKAP9, and ADAM10. This review provides an overview of the genetic basis of AD and the relationship between these risk genes and the neuropathologic features of AD. An understanding of genetic mechanisms underlying AD pathogenesis and the potentially implicated pathways will lead to the development of novel treatment for this devastating disease.

Alzheimer's Disease Risk Polymorphisms Regulate Gene Expression in the ZCWPW1 and the CELF1 Loci

Late onset Alzheimer’s disease (LOAD) is a genetically complex and clinically heterogeneous disease. Recent large-scale genome wide association studies (GWAS) have identified more than twenty loci that modify risk for AD. Despite the identification of these loci, little progress has been made in identifying the functional variants that explain the association with AD risk. Thus, we sought to determine whether the novel LOAD GWAS single nucleotide polymorphisms (SNPs) alter expression of LOAD GWAS genes and whether expression of these genes is altered in AD brains. The majority of LOAD GWAS SNPs occur in gene dense regions under large linkage disequilibrium (LD) blocks, making it unclear which gene(s) are modified by the SNP. Thus, we tested for brain expression quantitative trait loci (eQTLs) between LOAD GWAS SNPs and SNPs in high LD with the LOAD GWAS SNPs in all of the genes within the GWAS loci. We found a significant eQTL between rs1476679 and PILRB and GATS, which occurs within the ZCWPW1 locus. PILRB and GATS expression levels, within the ZCWPW1 locus, were also associated with AD status. Rs7120548 was associated with MTCH2 expression, which occurs within the CELF1 locus. Additionally, expression of several genes within the CELF1 locus, including MTCH2, were highly correlated with one another and were associated with AD status. We further demonstrate that PILRB, as well as other genes within the GWAS loci, are most highly expressed in microglia. These findings together with the function of PILRB as a DAP12 receptor supports the critical role of microglia and neuroinflammation in AD risk.

Verification of the Chromosome Region 9q21 Association with Pelvic Organ Prolapse Using RegulomeDB Annotations

Pelvic organ prolapse (POP) is a common highly disabling disorder with a large hereditary component. It is characterized by a loss of pelvic floor support that leads to the herniation of the uterus in or outside the vagina. Genome-wide linkage studies have shown an evidence of POP association with the region 9q21 and six other loci in European pedigrees. The aim of our study was to test the above associations in a case-control study in Russian population. Twelve SNPs including SNPs cited in the above studies and those selected using the RegulomeDB annotations for the region 9q21 were genotyped in 210 patients with POP (stages III-IV) and 292 controls with no even minimal POP. Genotyping was performed using the polymerase chain reaction with confronting two-pair primers (PCR–CTPP). Association analyses were conducted for individual SNPs, 9q21 haplotypes, and SNP-SNP interactions. SNP rs12237222 with the highest RegulomeDB score 1a appeared to be the key SNP in haplotypes associated with POP. Other RegulomeDB Category 1 SNPs, rs12551710 and rs2236479 (scores 1d and 1f, resp.), exhibited epistatic effects. In this study, we verified the region 9q21 association with POP in Russians, using RegulomeDB annotations.

Data interpretation: deciphering the biological function of Type 2 diabetes associated risk loci

AIMS

Type 2 diabetes (T2D) is a complex multifactorial disorder with more than 40 loci associated with disease susceptibility. Most of these genome-wide significant loci reside in noncoding regions, it is important to decipher the potential regulatory function of these variants and to differentiate between true and tag signals. Nowadays, databases are being developed to study and predict the function of these associated variants, and RegulomeDB is one such database.

METHODS

We used RegulomeDB to analyze the potential function of the associated variants reported in five genome-wide association studies (GWAS) of T2D.

RESULTS

We investigated the 1,567 single nucleotide polymorphisms (SNPs) with 989 SNPs with a score of 1-6. Of those 989 SNPs, only 64 returned with RegulomeDB score <3 (evidence of regulatory function), and only four of these were GWAS significant SNPs (THADA/rs10203174, score = 1b; UBE2E2/rs7612463, score = 2a; ARAP1/rs1552224 and TP53INP1/rs8996852, score = 2b). But only 63 % of the annotated SNPs showed regulatory function that is an important limitation of the RegulomeDB as this database only provides information of few regulatory elements.

CONCLUSION

This study further supports that some of the noncoding GWAS variants are the true associations and not the tag ones. This study also proves the utility and importance of the RegulomeDB and other such databases. Although it is an extensive database of regulatory elements but has certain limitation due to utilization of only few types of regulatory elements and pathways.

Genetic determinants of disease progression in Alzheimer's disease

There is a strong genetic basis for late-onset Alzheimer's disease (LOAD); thus far 22 genes/loci have been identified that affect the risk of LOAD. However, the relationships among the genetic variations at these loci and clinical progression of the disease have not been fully explored. In the present study, we examined the relationships of 22 known LOAD genes to the progression of AD in 680 AD patients recruited from the University of Pittsburgh Alzheimer's Disease Research Center. Patients were classified as "rapid progressors" if the Mini-Mental State Examination (MMSE) changed ≥3 points in 12 months and "slow progressors" if the MMSE changed ≤2 points. We also performed a genome-wide association study in this cohort in an effort to identify new loci for AD progression. Association analysis between single nucleotide polymorphisms (SNPs) and the progression status of the AD cases was performed using logistic regression model controlled for age, gender, dementia medication use, psychosis, and hypertension. While no significant association was observed with either APOE*4 (p = 0.94) or APOE*2 (p = 0.33) with AD progression, we found multiple nominally significant associations (p < 0.05) either within or adjacent to seven known LOAD genes (INPP5D, MEF2C, TREM2, EPHA1, PTK2B, FERMT2, and CASS4) that harbor both risk and protective SNPs. Genome-wide association analyses identified four suggestive loci (PAX3, CCRN4L, PIGQ, and ADAM19) at p < 1E-05. Our data suggest that short-term clinical disease progression in AD has a genetic basis. Better understanding of these genetic factors could help to improve clinical trial design and potentially affect the development of disease modifying therapies.

Embryonal Fyn-associated substrate (EFS) and CASS4: The lesser-known CAS protein family members

The CAS (Crk-associated substrate) adaptor protein family consists of four members: CASS1/BCAR1/p130Cas, CASS2/NEDD9/HEF1/Cas-L, CASS3/EFS/Sin and CASS4/HEPL. While CAS proteins lack enzymatic activity, they contain specific recognition and binding sites for assembly of larger signaling complexes that are essential for cell proliferation, survival, migration, and other processes. All family members are intermediates in integrin-dependent signaling pathways mediated at focal adhesions, and associate with FAK and SRC family kinases to activate downstream effectors regulating the actin cytoskeleton. Most studies of CAS proteins to date have been focused on the first two members, BCAR1 and NEDD9, with altered expression of these proteins now appreciated as influencing disease development and prognosis for cancer and other serious pathological conditions. For these family members, additional mechanisms of action have been defined in receptor tyrosine kinase (RTK) signaling, estrogen receptor signaling or cell cycle progression, involving discrete partner proteins such as SHC, NSP proteins, or AURKA. By contrast, EFS and CASS4 have been less studied, although structure-function analyses indicate they conserve many elements with the better-known family members. Intriguingly, a number of recent studies have implicated these proteins in immune system function, and the pathogenesis of developmental disorders, autoimmune disorders including Crohn's disease, Alzheimer's disease, cancer and other diseases. In this review, we summarize the current understanding of EFS and CASS4 protein function in the context of the larger CAS family group.

In-silico analysis of inflammatory bowel disease (IBD) GWAS loci to novel connections

Genome-wide association studies (GWASs) for many complex diseases, including inflammatory bowel disease (IBD), produced hundreds of disease-associated loci—the majority of which are noncoding. The number of GWAS loci is increasing very rapidly, but the process of translating single nucleotide polymorphisms (SNPs) from these loci to genomic medicine is lagging. In this study, we investigated 4,734 variants from 152 IBD associated GWAS loci (IBD associated 152 lead noncoding SNPs identified from pooled GWAS results + 4,582 variants in strong linkage-disequilibrium (LD) (r² ≥0.8) for EUR population of 1K Genomes Project) using four publicly available bioinformatics tools, e.g. dbPSHP, CADD, GWAVA, and RegulomeDB, to annotate and prioritize putative regulatory variants. Of the 152 lead noncoding SNPs, around 11% are under strong negative selection (GERP++ RS ≥2); and ~30% are under balancing selection (Tajima’s D score >2) in CEU population (1K Genomes Project)—though these regions are positively selected (GERP++ RS <0) in mammalian evolution. The analysis of 4,734 variants using three integrative annotation tools produced 929 putative functional SNPs, of which 18 SNPs (from 15 GWAS loci) are in concordance with all three classifiers. These prioritized noncoding SNPs may contribute to IBD pathogenesis by dysregulating the expression of nearby genes. This study showed the usefulness of integrative annotation for prioritizing fewer functional variants from a large number of GWAS markers.

Structural Neuroimaging Genetics Interactions in Alzheimer's Disease

This article investigates late-onset cognitive impairment using neuroimaging and genetics biomarkers for Alzheimer's Disease Neuroimaging Initiative (ADNI) participants. Eight-hundred and eight ADNI subjects were identified and divided into three groups: 200 subjects with Alzheimer's disease (AD), 383 subjects with mild cognitive impairment (MCI), and 225 asymptomatic normal controls (NC). Their structural magnetic resonance imaging (MRI) data were parcellated using BrainParser, and the 80 most important neuroimaging biomarkers were extracted using the global shape analysis Pipeline workflow. Using Plink via the Pipeline environment, we obtained 80 SNPs highly-associated with the imaging biomarkers. In the AD cohort, rs2137962 was significantly associated bilaterally with changes in the hippocampi and the parahippocampal gyri, and rs1498853, rs288503, and rs288496 were associated with the left and right hippocampi, the right parahippocampal gyrus, and the left inferior temporal gyrus. In the MCI cohort, rs17028008 and rs17027976 were significantly associated with the right caudate and right fusiform gyrus, rs2075650 (TOMM40) was associated with the right caudate, and rs1334496 and rs4829605 were significantly associated with the right inferior temporal gyrus. In the NC cohort, Chromosome 15 [rs734854 (STOML1), rs11072463 (PML), rs4886844 (PML), and rs1052242 (PML)] was significantly associated with both hippocampi and both insular cortices, and rs4899412 (RGS6) was significantly associated with the caudate. We observed significant correlations between genetic and neuroimaging phenotypes in the 808 ADNI subjects. These results suggest that differences between AD, MCI, and NC cohorts may be examined by using powerful joint models of morphometric, imaging and genotypic data.

Putative functional variants of XRCC1 identified by RegulomeDB were not associated with lung cancer risk in a Korean population

The Encyclopedia of DNA elements (ENCODE) project revealed that nearby or distantly located non-coding DNA regulates the expression of coding genes. RegulomeDB (http://regulome.stanford.edu) is a new database that can be used to predict whether a variant affects transcription factor binding and gene expression. We investigated the association between lung cancer risk and potentially functional polymorphisms of XRCC1 that were selected using RegulomeDB in a Korean population. A total of 185 polymorphisms of XRCC1 were evaluated using RegulomeDB. Strong evidence suggested that 10 polymorphisms, from among the 185, affected XRCC1 expression with scores of 1a-1f that were based on the RegulomeDB scoring system. The rs2854510 polymorphism was rare in Asians (minor allele frequency < 0.05). Eight polymorphisms were in strong linkage disequilibrium (LD). The rs2854509 polymorphism, which was one of the 8 polymorphisms in LD, and rs7248167, which was not in the LD block, were genotyped in 610 lung cancer patients and 607 age- and sex-matched controls. Additionally, four polymorphisms of XRCC1 (rs25487, rs25489, rs1799782, and rs3213245), which were investigated with regard to their association with lung cancer risk in previous studies, were also genotyped. Two polymorphisms (rs2854509 and rs7248167) that were predicted to affect XRCC1 expression based on their RegulomeDB scores were not associated with lung cancer risk (P = 0.31 and 0.93, respectively). When stratified according to age, gender, smoking status, and tumor histology, the two polymorphisms of XRCC1 were not associated with lung cancer risk. Among the four polymorphisms that were previously studied, only rs25489 of XRCC1 was significantly associated with lung cancer risk (dominant model, adjusted odds ratio = 0.61, 95% confidence interval = 0.46-0.83, P = 0.002). Although RegulomeDB is an attractive tool for predicting the regulatory potential of variants, the two polymorphisms that were selected using RegulomeDB were not associated with lung cancer risk.