Whole-exome sequencing and imaging genetics identify functional variants for rate of change in hippocampal volume in mild cognitive impairment

PARP-1 gene promoter region may be associated with progression in multiple sclerosis

Multiple Sclerosis (MS) is a leading cause of disability among young adults. Most cases begin with relapsing-remitting MS (RRMS) and can transition to secondary progressive MS (SPMS) over time. It is known that the inflammatory status of the central nervous system changes during the progression of MS. Poly (ADP-ribose) polymerase-1 (PARP-1) is an enzyme involved in several cellular processes. Our study aimed to investigate the relationship between MS and the PARP-1 gene. We analyzed the PARP-1 gene's missense polymorphism rs1136410, promoter region polymorphism rs7527192, and 3'UTR polymorphism rs8679 in 123 MS patients and 168 healthy controls using the PCR-RFLP method. We examined genotype and allele frequency distributions among case-control groups and clinical subgroups. We observed that the CC genotype of rs7527192 polymorphism was increased in SPMS patients compared to controls. We also found that the CC genotype and C allele frequency were increased in the EDSS score > 3-6 group compared to healthy controls. The C allele frequency was increased in EDSS score > 3-6 compared to those with ≤ 3 and ≥ 6. When the results observed in our study are evaluated with the known effect of PARP-1 on the inflammasome pathway, we suggest that rs7527192 may be effective in the progression process through the activity of the PARP-1 inflammasome pathway.

Risk Factors, Pathological Changes, and Potential Treatment of Diabetes-Associated Cognitive Dysfunction

BACKGROUND

Diabetes is a prevalent public health issue worldwide, and the cognitive dysfunction and subsequent dementia caused by it seriously affect the quality of life of patients.

METHODS

Recent studies were reviewed to provide a comprehensive summary of the risk factors, pathogenesis, pathological changes and potential drug treatments for diabetes-related cognitive dysfunction (DACD).

RESULTS

Several risk factors contribute to DACD, including hyperglycemia, hypoglycemia, blood sugar fluctuations, hyperinsulinemia, aging, and others. Among them, modifiable risk factors for DACD include blood glucose control, physical activity, diet, smoking, and hypertension management, while non-modifiable risk factors include age, genetic predisposition, sex, and duration of diabetes. At the present, the pathogenesis of DACD mainly includes insulin resistance, neuroinflammation, vascular disorders, oxidative stress, and neurotransmitter disorders.

CONCLUSIONS

In this review, we provide a comprehensive summary of the risk factors, pathogenesis, pathological changes and potential drug treatments for DACD, providing information from multiple perspectives for its prevention and management.

Novel Genes Associated With Working Memory Are Identified by Combining Connectome, Transcriptome, and Genome

Working memory (WM) plays a crucial role in human cognition. Previous candidate and genome-wide association studies have reported many genetic variations associated with WM. However, little research has examined genetic basis of WM by using transcriptome, even though it reflects gene function more directly than does the genome. Here we propose a new approach to exploring the genetic mechanisms of WM by integrating connectome, transcriptome, and genome data in a high-quality dataset comprising 481 Chinese healthy adults. First, relevance vector regression was used to define WM-related brain regions. Second, genes differentially expressed within these regions were identified using the Allen Human Brain Atlas (AHBA) dataset. Finally, two independent datasets were used to validate these genes' contributions to WM. With this method, we identified 24 novel genes and 20 of them were confirmed in the large-scale datasets of ABCD and UK Biobank. These novel genes were enriched in the cellular component of collagen-containing extracellular matrix and the CCL18 signaling pathway. Our method offers an effective approach to integrating multimodal gene discovery and demonstrates the superiority of expression data. This new method and the newly identified genes deserve more attention in the future.

Consistent genes associated with structural changes in clinical Alzheimer's disease spectrum

Background

Previous studies have demonstrated widespread brain neurodegeneration in Alzheimer's disease (AD). However, the neurobiological and pathogenic substrates underlying this structural atrophy across the AD spectrum remain largely understood.

Methods

In this study, we obtained structural MRI data from ADNI datasets, including 83 participants with early-stage cognitive impairments (EMCI), 83 with late-stage mild cognitive impairments (LMCI), 83 with AD, and 83 with normal controls (NC). Our goal was to explore structural atrophy across the full clinical AD spectrum and investigate the genetic mechanism using gene expression data from the Allen Human Brain Atlas.

Results

As a result, we identified significant volume atrophy in the left thalamus, left cerebellum, and bilateral middle frontal gyrus across the AD spectrum. These structural changes were positively associated with the expression levels of genes such as ABCA7, SORCS1, SORL1, PILRA, PFDN1, PLXNA4, TRIP4, and CD2AP, while they were negatively associated with the expression levels of genes such as CD33, PLCG2, APOE, and ECHDC3 across the clinical AD spectrum. Further gene enrichment analyses revealed that the positively associated genes were mainly involved in the positive regulation of cellular protein localization and the negative regulation of cellular component organization, whereas the negatively associated genes were mainly involved in the positive regulation of iron transport.

Conclusion

Overall, these results provide a deeper understanding of the biological mechanisms underlying structural changes in prodromal and clinical AD.

CYP1B1-RMDN2 Alzheimer's disease endophenotype locus identified for cerebral tau PET

Determining the genetic architecture of Alzheimer's disease pathologies can enhance mechanistic understanding and inform precision medicine strategies. Here, we perform a genome-wide association study of cortical tau quantified by positron emission tomography in 3046 participants from 12 independent studies. The CYP1B1-RMDN2 locus is associated with tau deposition. The most significant signal is at rs2113389, explaining 4.3% of the variation in cortical tau, while APOE4 rs429358 accounts for 3.6%. rs2113389 is associated with higher tau and faster cognitive decline. Additive effects, but no interactions, are observed between rs2113389 and diagnosis, APOE4, and amyloid beta positivity. CYP1B1 expression is upregulated in AD. rs2113389 is associated with higher CYP1B1 expression and methylation levels. Mouse model studies provide additional functional evidence for a relationship between CYP1B1 and tau deposition but not amyloid beta. These results provide insight into the genetic basis of cerebral tau deposition and support novel pathways for therapeutic development in AD.

BayesKAT: bayesian optimal kernel-based test for genetic association studies reveals joint genetic effects in complex diseases

Genome-wide Association Studies (GWAS) methods have identified individual single-nucleotide polymorphisms (SNPs) significantly associated with specific phenotypes. Nonetheless, many complex diseases are polygenic and are controlled by multiple genetic variants that are usually non-linearly dependent. These genetic variants are marginally less effective and remain undetected in GWAS analysis. Kernel-based tests (KBT), which evaluate the joint effect of a group of genetic variants, are therefore critical for complex disease analysis. However, choosing different kernel functions in KBT can significantly influence the type I error control and power, and selecting the optimal kernel remains a statistically challenging task. A few existing methods suffer from inflated type 1 errors, limited scalability, inferior power or issues of ambiguous conclusions. Here, we present a new Bayesian framework, BayesKAT (https://github.com/wangjr03/BayesKAT), which overcomes these kernel specification issues by selecting the optimal composite kernel adaptively from the data while testing genetic associations simultaneously. Furthermore, BayesKAT implements a scalable computational strategy to boost its applicability, especially for high-dimensional cases where other methods become less effective. Based on a series of performance comparisons using both simulated and real large-scale genetics data, BayesKAT outperforms the available methods in detecting complex group-level associations and controlling type I errors simultaneously. Applied on a variety of groups of functionally related genetic variants based on biological pathways, co-expression gene modules and protein complexes, BayesKAT deciphers the complex genetic basis and provides mechanistic insights into human diseases.

A Review of PARP-1 Inhibitors: Assessing Emerging Prospects and Tailoring Therapeutic Strategies

Eukaryotic organisms contain an enzyme family called poly (ADP-ribose) polymerases (PARPs), which is responsible for the poly (ADP-ribosylation) of DNA-binding proteins. PARPs are members of the cell signaling enzyme class. PARP-1, the most common isoform of the PARP family, is responsible for more than 90% of the tasks carried out by the PARP family as a whole. A superfamily consisting of 18 PARPs has been found. In order to synthesize polymers of ADP-ribose (PAR) and nicotinamide, the DNA damage nick monitor PARP-1 requires NAD+ as a substrate. The capability of PARP-1 activation to boost the transcription of proinflammatory genes, its ability to deplete cellular energy pools, which leads to cell malfunction and necrosis, and its involvement as a component in the process of DNA repair are the three consequences of PARP-1 activation that are of particular significance in the process of developing new drugs. As a result, the pharmacological reduction of PARP-1 may result in an increase in the cytotoxicity toward cancer cells.

BayesKAT: Bayesian Optimal Kernel-based Test for genetic association studies reveals joint genetic effects in complex diseases

GWAS methods have identified individual SNPs significantly associated with specific phenotypes. Nonetheless, many complex diseases are polygenic and are controlled by multiple genetic variants that are usually non-linearly dependent. These genetic variants are marginally less effective and remain undetected in GWAS analysis. Kernel-based tests (KBT), which evaluate the joint effect of a group of genetic variants, are therefore critical for complex disease analysis. However, choosing different kernel functions in KBT can significantly influence the type I error control and power, and selecting the optimal kernel remains a statistically challenging task. A few existing methods suffer from inflated type 1 errors, limited scalability, inferior power, or issues of ambiguous conclusions. Here, we present a new Bayesian framework, BayesKAT( https://github.com/wangjr03/BayesKAT ), which overcomes these kernel specification issues by selecting the optimal composite kernel adaptively from the data while testing genetic associations simultaneously. Furthermore, BayesKAT implements a scalable computational strategy to boost its applicability, especially for high-dimensional cases where other methods become less effective. Based on a series of performance comparisons using both simulated and real large-scale genetics data, BayesKAT outperforms the available methods in detecting complex group-level associations and controlling type I errors simultaneously. Applied on a variety of groups of functionally related genetic variants based on biological pathways, co-expression gene modules, and protein complexes, BayesKAT deciphers the complex genetic basis and provides mechanistic insights into human diseases.

Novel CYP1B1-RMDN2 Alzheimer's disease locus identified by genome-wide association analysis of cerebral tau deposition on PET

Determining the genetic architecture of Alzheimer's disease (AD) pathologies can enhance mechanistic understanding and inform precision medicine strategies. Here, we performed a genome-wide association study of cortical tau quantified by positron emission tomography in 3,136 participants from 12 independent studies. The CYP1B1-RMDN2 locus was associated with tau deposition. The most significant signal was at rs2113389, which explained 4.3% of the variation in cortical tau, while APOE4 rs429358 accounted for 3.6%. rs2113389 was associated with higher tau and faster cognitive decline. Additive effects, but no interactions, were observed between rs2113389 and diagnosis, APOE4 , and Aβ positivity. CYP1B1 expression was upregulated in AD. rs2113389 was associated with higher CYP1B1 expression and methylation levels. Mouse model studies provided additional functional evidence for a relationship between CYP1B1 and tau deposition but not Aβ. These results may provide insight into the genetic basis of cerebral tau and novel pathways for therapeutic development in AD.

CARMA3: A potential therapeutic target in non-cancer diseases

Caspase recruitment domain and membrane-associated guanylate kinase-like protein 3 (CARMA3) is a scaffold protein widely expressed in non-hematopoietic cells. It is encoded by the caspase recruitment domain protein 10 (CARD10) gene. CARMA3 can form a CARMA3-BCL10-MALT1 complex by recruiting B cell lymphoma 10 (BCL10) and mucosa-​associated lymphoid tissue lymphoma translocation protein 1 (MALT1), thereby activating nuclear factor-​κB (NF-κB), a key transcription factor that involves in various biological responses. CARMA3 mediates different receptors-dependent signaling pathways, including G protein-coupled receptors (GPCRs) and receptor tyrosine kinases (RTKs). Inappropriate expression and activation of GPCRs and/or RTKs/CARMA3 signaling lead to the pathogenesis of human diseases. Emerging studies have reported that CARMA3 mediates the development of various types of cancers. Moreover, CARMA3 and its partners participate in human non-cancer diseases, including atherogenesis, abdominal aortic aneurysm, asthma, pulmonary fibrosis, liver fibrosis, insulin resistance, inflammatory bowel disease, and psoriasis. Here we provide a review on its structure, regulation, and molecular function, and further highlight recent findings in human non-cancerous diseases, which will provide a novel therapeutic target.

Rare variants in IFFO1, DTNB, NLRC3 and SLC22A10 associate with Alzheimer's disease CSF profile of neuronal injury and inflammation

Alzheimer's disease (AD) biomarkers represent several neurodegenerative processes, such as synaptic dysfunction, neuronal inflammation and injury, as well as amyloid pathology. We performed an exome-wide rare variant analysis of six AD biomarkers (β-amyloid, total/phosphorylated tau, NfL, YKL-40, and Neurogranin) to discover genes associated with these markers. Genetic and biomarker information was available for 480 participants from two studies: EMIF-AD and ADNI. We applied a principal component (PC) analysis to derive biomarkers combinations, which represent statistically independent biological processes. We then tested whether rare variants in 9576 protein-coding genes associate with these PCs using a Meta-SKAT test. We also tested whether the PCs are intermediary to gene effects on AD symptoms with a SMUT test. One PC loaded on NfL and YKL-40, indicators of neuronal injury and inflammation. Four genes were associated with this PC: IFFO1, DTNB, NLRC3, and SLC22A10. Mediation tests suggest, that these genes also affect dementia symptoms via inflammation/injury. We also observed an association between a PC loading on Neurogranin, a marker for synaptic functioning, with GABBR2 and CASZ1, but no mediation effects. The results suggest that rare variants in IFFO1, DTNB, NLRC3, and SLC22A10 heighten susceptibility to neuronal injury and inflammation, potentially by altering cytoskeleton structure and immune activity disinhibition, resulting in an elevated dementia risk. GABBR2 and CASZ1 were associated with synaptic functioning, but mediation analyses suggest that the effect of these two genes on synaptic functioning is not consequential for AD development.

The role of PARP1 in neurodegenerative diseases and aging

Neurodegenerative diseases, including Alzheimer's disease (AD) and Parkinson's disease (PD), are characterized by progressive memory loss and motor impairment. Aging is a major risk factor for neurodegenerative diseases. Neurodegenerative diseases and aging often develop in an irreversible manner and cause a significant socioeconomic burden. When considering their pathogenesis, many studies usually focus on mitochondrial dysfunction and DNA damage. More recently, neuroinflammation, autophagy dysregulation, and SIRT1 inactivation were shown to be involved in the pathogenesis of neurodegenerative diseases and aging. In addition, studies uncovered the role of poly (ADP-ribose)-polymerase-1 (PARP1) in neurodegenerative diseases and aging. PARP1 links to a cluster of stress signals, including those originated by inflammation and autophagy dysregulation. In this review, we summarized the recent research progresses on PARP1 in neurodegenerative diseases and aging, with an emphasis on the relationship among PARP1, neuroinflammation, mitochondria, and autophagy. We discussed the possibilities of treating neurodegenerative diseases and aging through targeting PARP1.

Pharmacogenetic Analyses of Therapeutic Effects of Lipophilic Statins on Cognitive and Functional Changes in Alzheimer’s Disease

Background: Pharmacogenetic effects of statins on clinical changes in Alzheimer’s disease (AD) could be mediated by epistatic interactions among relevant genetic variants involved in cholesterol metabolism. Objective: To investigate associations of HMGCR (rs3846662), NR1H2 (rs2695121), or CETP (rs5882&rs708272) with cognitive and functional changes in AD, with stratification according to APOE ɛ4 carrier status and lipid-lowering treatment with lipophilic statins. Methods: Consecutive outpatients with late-onset AD were screened with cognitive tests, while caregivers scored functionality and global ratings, with prospective neurotranslational associations documented for one year. Results: Considering n = 190:142 had hypercholesterolemia, 139 used lipophilic statins; minor allele frequencies were 0.379 (rs2695121-T:46.3% heterozygotes), 0.368 (rs5882-G:49.5% heterozygotes), and 0.371 (rs708272-A:53.2% heterozygotes), all in Hardy-Weinberg equilibrium. For APOE ɛ4 carriers: rs5882-GG protected from cognitive decline; rs5882-AA caused faster cognitive decline; carriers of rs2695121-CC or rs5882-AA were more susceptible to harmful cognitive effects of lipophilic statins; carriers of rs5882-GG or rs708272-AG had functional benefits when using lipophilic statins. APOE ɛ4 non-carriers resisted any cognitive or functional effects of lipophilic statins, while invariability of rs3846662 (all AA) prevented the assessment of HMGCR effects. When assessing CETP haplotypes only: rs5882-GG protected from cognitive and functional decline, regardless of lipophilic statin therapy; lipophilic statins usually caused cognitive and functional harm to carriers of rs5882-A and/or rs708272-A; lipophilic statins benefitted cognition and functionality of carriers of rs5882-G and/or rs708272-G. Conclusion: Reportedly protective variants of CETP and NR1H2 also slowed cognitive and functional decline particularly for APOE ɛ4 carriers, and regardless of cholesterol variations, while therapy with lipophilic statins might affect carriers of specific genetic variants.

The Complex Mechanisms by Which Neurons Die Following DNA Damage in Neurodegenerative Diseases

Human cells are exposed to numerous exogenous and endogenous insults every day. Unlike other molecules, DNA cannot be replaced by resynthesis, hence damage to DNA can have major consequences for the cell. The DNA damage response contains overlapping signalling networks that repair DNA and hence maintain genomic integrity, and aberrant DNA damage responses are increasingly described in neurodegenerative diseases. Furthermore, DNA repair declines during aging, which is the biggest risk factor for these conditions. If unrepaired, the accumulation of DNA damage results in death to eliminate cells with defective genomes. This is particularly important for postmitotic neurons because they have a limited capacity to proliferate, thus they must be maintained for life. Neuronal death is thus an important process in neurodegenerative disorders. In addition, the inability of neurons to divide renders them susceptible to senescence or re-entry to the cell cycle. The field of cell death has expanded significantly in recent years, and many new mechanisms have been described in various cell types, including neurons. Several of these mechanisms are linked to DNA damage. In this review, we provide an overview of the cell death pathways induced by DNA damage that are relevant to neurons and discuss the possible involvement of these mechanisms in neurodegenerative conditions.

Integrative-omics for discovery of network-level disease biomarkers: a case study in Alzheimer's disease

A large number of genetic variations have been identified to be associated with Alzheimer's disease (AD) and related quantitative traits. However, majority of existing studies focused on single types of omics data, lacking the power of generating a community including multi-omic markers and their functional connections. Because of this, the immense value of multi-omics data on AD has attracted much attention. Leveraging genomic, transcriptomic and proteomic data, and their backbone network through functional relations, we proposed a modularity-constrained logistic regression model to mine the association between disease status and a group of functionally connected multi-omic features, i.e. single-nucleotide polymorphisms (SNPs), genes and proteins. This new model was applied to the real data collected from the frontal cortex tissue in the Religious Orders Study and Memory and Aging Project cohort. Compared with other state-of-art methods, it provided overall the best prediction performance during cross-validation. This new method helped identify a group of densely connected SNPs, genes and proteins predictive of AD status. These SNPs are mostly expression quantitative trait loci in the frontal region. Brain-wide gene expression profile of these genes and proteins were highly correlated with the brain activation map of 'vision', a brain function partly controlled by frontal cortex. These genes and proteins were also found to be associated with the amyloid deposition, cortical volume and average thickness of frontal regions. Taken together, these results suggested a potential pathway underlying the development of AD from SNPs to gene expression, protein expression and ultimately brain functional and structural changes.

Rare CASP6N73T variant associated with hippocampal volume exhibits decreased proteolytic activity, synaptic transmission defect, and neurodegeneration

Caspase-6 (Casp6) is implicated in Alzheimer disease (AD) cognitive impairment and pathology. Hippocampal atrophy is associated with cognitive impairment in AD. Here, a rare functional exonic missense CASP6 single nucleotide polymorphism (SNP), causing the substitution of asparagine with threonine at amino acid 73 in Casp6 (Casp6N73T), was associated with hippocampal subfield CA1 volume preservation. Compared to wild type Casp6 (Casp6WT), recombinant Casp6N73T altered Casp6 proteolysis of natural substrates Lamin A/C and α-Tubulin, but did not alter cleavage of the Ac-VEID-AFC Casp6 peptide substrate. Casp6N73T-transfected HEK293T cells showed elevated Casp6 mRNA levels similar to Casp6WT-transfected cells, but, in contrast to Casp6WT, did not accumulate active Casp6 subunits nor show increased Casp6 enzymatic activity. Electrophysiological and morphological assessments showed that Casp6N73T recombinant protein caused less neurofunctional damage and neurodegeneration in hippocampal CA1 pyramidal neurons than Casp6WT. Lastly, CASP6 mRNA levels were increased in several AD brain regions confirming the implication of Casp6 in AD. These studies suggest that the rare Casp6N73T variant may protect against hippocampal atrophy due to its altered catalysis of natural protein substrates and intracellular instability thus leading to less Casp6-mediated damage to neuronal structure and function.

Molecular Genetics of Early- and Late-Onset Alzheimer's Disease

Alzheimer's disease (AD) is the most common form of dementia in the elderly and this complex disorder is associated with environmental as well as genetic factors. Early-onset AD (EOAD) and late-onset AD (LOAD, more common) are major identified types of AD. The genetics of EOAD is extensively understood, with three gene variants such as APP, PSEN1, and PSEN2 leading to the disease. Some common alleles, including APOE, are effectively associated with LOAD identified, but the genetics of LOAD is not clear to date. It has been accounted that about 5-10% of EOAD patients can be explained through mutations in the three familiar genes of EOAD. The APOE ε4 allele augmented the severity of EOAD risk in carriers, and the APOE ε4 allele was considered as a hallmark of EOAD. A great number of EOAD patients, who are not genetically explained, indicate that it is not possible to identify disease-triggering genes yet. Although several genes have been identified by using the technology of next-generation sequencing in EOAD families, including SORL1, TYROBP, and NOTCH3. A number of TYROBP variants are identified through exome sequencing in EOAD patients and these TYROBP variants may increase the pathogenesis of EOAD. The existence of the ε4 allele is responsible for increasing the severity of EOAD. However, several ε4 allele carriers propose the presence of other LOAD genetic as well as environmental risk factors that are not identified yet. It is urgent to find out missing genetics of EOAD and LOAD etiology to discover new potential genetic facets which will assist in understanding the pathological mechanism of AD. These investigations should contribute to developing a new therapeutic candidate for alleviating, reversing and preventing AD. This article, based on current knowledge, represents the overview of the susceptible genes of EOAD, and LOAD. Next, we represent the probable molecular mechanism that might elucidate the genetic etiology of AD and highlight the role of massively parallel sequencing technologies for novel gene discoveries.

MicroRNA-298 reduces levels of human amyloid-β precursor protein (APP), β-site APP-converting enzyme 1 (BACE1) and specific tau protein moieties

Alzheimer's disease (AD) is the most common age-related form of dementia, associated with deposition of intracellular neuronal tangles consisting primarily of hyperphosphorylated microtubule-associated protein tau (p-tau) and extracellular plaques primarily comprising amyloid- β (Aβ) peptide. The p-tau tangle unit is a posttranslational modification of normal tau protein. Aβ is a neurotoxic peptide excised from the amyloid-β precursor protein (APP) by β-site APP-cleaving enzyme 1 (BACE1) and the γ-secretase complex. MicroRNAs (miRNAs) are short, single-stranded RNAs that modulate protein expression as part of the RNA-induced silencing complex (RISC). We identified miR-298 as a repressor of APP, BACE1, and the two primary forms of Aβ (Aβ40 and Aβ42) in a primary human cell culture model. Further, we discovered a novel effect of miR-298 on posttranslational levels of two specific tau moieties. Notably, miR-298 significantly reduced levels of ~55 and 50 kDa forms of the tau protein without significant alterations of total tau or other forms. In vivo overexpression of human miR-298 resulted in nonsignificant reduction of APP, BACE1, and tau in mice. Moreover, we identified two miR-298 SNPs associated with higher cerebrospinal fluid (CSF) p-tau and lower CSF Aβ42 levels in a cohort of human AD patients. Finally, levels of miR-298 varied in postmortem human temporal lobe between AD patients and age-matched non-AD controls. Our results suggest that miR-298 may be a suitable target for AD therapy.

Genetic testing in dementia - utility and clinical strategies

Techniques for clinical genetic testing in dementia disorders have advanced rapidly but remain to be more widely implemented in practice. A positive genetic test offers a precise molecular diagnosis, can help members of an affected family to determine personal risk, provides a basis for reproductive choices and can offer options for clinical trials. The likelihood of identifying a specific genetic cause of dementia depends on the clinical condition, the age at onset and family history. Attempts to match phenotypes to single genes are mostly inadvisable owing to clinical overlap between the dementias, genetic heterogeneity, pleiotropy and concurrent mutations. Currently, the appropriate genetic test in most cases of dementia is a next-generation sequencing gene panel, though some conditions necessitate specific types of test such as repeat expansion testing. Whole-exome and whole-genome sequencing are becoming financially feasible but raise or exacerbate complex issues such as variants of uncertain significance, secondary findings and the potential for re-analysis in light of new information. However, the capacity for data analysis and counselling is already restricting the provision of genetic testing. Patients and their relatives need to be given reliable information to enable them to make informed choices about tests, treatments and data sharing; the ability of patients with dementia to make decisions must be considered when providing this information.

Volumetric GWAS of medial temporal lobe structures identifies an ERC1 locus using ADNI high-resolution T2-weighted MRI data

Medial temporal lobe (MTL) consists of hippocampal subfields and neighboring cortices. These heterogeneous structures are differentially involved in memory, cognitive and emotional functions, and present nonuniformly distributed atrophy contributing to cognitive disorders. This study aims to examine how genetics influences Alzheimer's disease (AD) pathogenesis via MTL substructures by analyzing high-resolution magnetic resonance imaging (MRI) data. We performed genome-wide association study to examine the associations between 565,373 single nucleotide polymorphisms (SNPs) and 14 MTL substructure volumes. A novel association with right Brodmann area 36 volume was discovered in an ERC1 SNP (i.e., rs2968869). Further analyses on larger samples found rs2968869 to be associated with gray matter density and glucose metabolism measures in the right hippocampus, and disease status. Tissue-specific transcriptomic analysis identified the minor allele of rs2968869 (rs2968869-C) to be associated with reduced ERC1 expression in the hippocampus. All the findings indicated a protective role of rs2968869-C in AD. We demonstrated the power of high-resolution MRI and the promise of fine-grained MTL substructures for revealing the genetic basis of AD biomarkers.

Genome-wide transcriptome analysis identifies novel dysregulated genes implicated in Alzheimer's pathology

INTRODUCTION

Abnormal gene expression patterns may contribute to the onset and progression of late-onset Alzheimer's disease (LOAD).

METHODS

We performed transcriptome-wide meta-analysis (N = 1440) of blood-based microarray gene expression profiles as well as neuroimaging and cerebrospinal fluid (CSF) endophenotype analysis.

RESULTS

We identified and replicated five genes (CREB5, CD46, TMBIM6, IRAK3, and RPAIN) as significantly dysregulated in LOAD. The most significantly altered gene, CREB5, was also associated with brain atrophy and increased amyloid beta (Aβ) accumulation, especially in the entorhinal cortex region. cis-expression quantitative trait loci mapping analysis of CREB5 detected five significant associations (P < 5 × 10^-8 ), where rs56388170 (most significant) was also significantly associated with global cortical Aβ deposition measured by [¹⁸ F]Florbetapir positron emission tomography and CSF Aβ_1-42 .

DISCUSSION

RNA from peripheral blood indicated a differential gene expression pattern in LOAD. Genes identified have been implicated in biological processes relevant to Alzheimer's disease. CREB, in particular, plays a key role in nervous system development, cell survival, plasticity, and learning and memory.

Identification of functionally connected multi-omic biomarkers for Alzheimer's disease using modularity-constrained Lasso

Large-scale genome wide association studies (GWASs) have led to discovery of many genetic risk factors in Alzheimer's disease (AD), such as APOE, TOMM40 and CLU. Despite the significant progress, it remains a major challenge to functionally validate these genetic findings and translate them into targetable mechanisms. Integration of multiple types of molecular data is increasingly used to address this problem. In this paper, we proposed a modularity-constrained Lasso model to jointly analyze the genotype, gene expression and protein expression data for discovery of functionally connected multi-omic biomarkers in AD. With a prior network capturing the functional relationship between SNPs, genes and proteins, the newly introduced penalty term maximizes the global modularity of the subnetwork involving selected markers and encourages the selection of multi-omic markers with dense functional connectivity, instead of individual markers. We applied this new model to the real data collected in the ROS/MAP cohort where the cognitive performance was used as disease quantitative trait. A functionally connected subnetwork involving 276 multi-omic biomarkers, including SNPs, genes and proteins, were identified to bear predictive power. Within this subnetwork, multiple trans-omic paths from SNPs to genes and then proteins were observed. This suggests that cognitive performance deterioration in AD patients can be potentially a result of genetic variations due to their cascade effect on the downstream transcriptome and proteome level.

Brain-wide structural connectivity alterations under the control of Alzheimer risk genes

Background

Alzheimer's disease is the most common form of brain dementia characterized by gradual loss of memory followed by further deterioration of other cognitive function. Large-scale genome-wide association studies have identified and validated more than 20 AD risk genes. However, how these genes are related to the brain-wide breakdown of structural connectivity in AD patients remains unknown.

Methods

We used the genotype and DTI data in the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. After constructing the brain network for each subject, we extracted three types of link measures, including fiber anisotropy, fiber length and density. We then performed a targeted genetic association analysis of brain-wide connectivity measures using general linear regression models. Age at scan and gender were included in the regression model as covariates. For fair comparison of the genetic effect on different measures, fiber anisotropy, fiber length and density were all normalized with mean as 0 and standard deviation as one.We aim to discover the abnormal brain-wide network alterations under the control of 34 AD risk SNPs identified in previous large-scale genome-wide association studies.

Results

After enforcing the stringent Bonferroni correction, rs10498633 in SLC24A4 were found to significantly associated with anisotropy, total number and length of fibers, including some connecting brain hemispheres. With a lower level of significance at 5e-6, we observed significant genetic effect of SNPs in APOE, ABCA7, EPHA1 and CASS4 on various brain connectivity measures.

Validity Evidences of the Prefrontal Symptoms Inventory for the Elderly Brazilian Population

OBJECTIVES

This study aimed to translate the Prefrontal Symptoms Inventory (PSI) (abbreviated version) for the elderly into Brazilian Portuguese, evaluate its psychometric properties, and investigate if the PSI could distinguish between groups with (clinical group) and without (non-clinical group) a diagnosis of probable Alzheimer's disease (AD).

METHODS

The PSI was idiomatically and culturally adapted, and then administered to 256 individuals over 60 years of age who also completed a clinical interview, the Mini-Mental State Examination (MMSE), the Geriatric Depression Scale (GDS)-15, and the Frontal Assessment Battery (FAB).

RESULTS

The results indicated satisfactory adjustment and adequate reliability (Ω of 0.83 and α=0.80) for the uni-factorial model. The non-clinical group showed significant correlations between the PSI-16, GDS-15, MMSE, and FAB and its six subtests. In the clinical group, there were negative correlations between the PSI-16, MMSE, and the FAB and the conceptual subtest. The groups differed statistically significantly, with the clinical sample showing the highest PSI-16 score. In the non-clinical group, there were significant positive correlations between age and PSI-16, and negative correlations between education and PSI-16.

CONCLUSION

The results of this study indicate that the PSI-16 can be used as a valid and reliable screening tool for clinical use in the elderly with and without pathology.

Brain Imaging Genomics: Integrated Analysis and Machine Learning

Brain imaging genomics is an emerging data science field, where integrated analysis of brain imaging and genomics data, often combined with other biomarker, clinical and environmental data, is performed to gain new insights into the phenotypic, genetic and molecular characteristics of the brain as well as their impact on normal and disordered brain function and behavior. It has enormous potential to contribute significantly to biomedical discoveries in brain science. Given the increasingly important role of statistical and machine learning in biomedicine and rapidly growing literature in brain imaging genomics, we provide an up-to-date and comprehensive review of statistical and machine learning methods for brain imaging genomics, as well as a practical discussion on method selection for various biomedical applications.

Exonic Variants in Aging-Related Genes Are Predictive of Phenotypic Aging Status

Background: Recent studies investigating longevity have revealed very few convincing genetic associations with increased lifespan. This is, in part, due to the complexity of biological aging, as well as the limited power of genome-wide association studies, which assay common single nucleotide polymorphisms (SNPs) and require several thousand subjects to achieve statistical significance. To overcome such barriers, we performed comprehensive DNA sequencing of a panel of 20 genes previously associated with phenotypic aging in a cohort of 200 individuals, half of whom were clinically defined by an "early aging" phenotype, and half of whom were clinically defined by a "late aging" phenotype based on age (65-75 years) and the ability to walk up a flight of stairs or walk for 15 min without resting. A validation cohort of 511 late agers was used to verify our results. Results: We found early agers were not enriched for more total variants in these 20 aging-related genes than late agers. Using machine learning methods, we identified the most predictive model of aging status, both in our discovery and validation cohorts, to be a random forest model incorporating damaging exon variants [Combined Annotation-Dependent Depletion (CADD) > 15]. The most heavily weighted variants in the model were within poly(ADP-ribose) polymerase 1 (PARP1) and excision repair cross complementation group 5 (ERCC5), both of which are involved in a canonical aging pathway, DNA damage repair. Conclusion: Overall, this study implemented a framework to apply machine learning to identify sequencing variants associated with complex phenotypes such as aging. While the small sample size making up our cohort inhibits our ability to make definitive conclusions about the ability of these genes to accurately predict aging, this study offers a unique method for exploring polygenic associations with complex phenotypes.

Genome-wide association analysis of hippocampal volume identifies enrichment of neurogenesis-related pathways

Adult neurogenesis occurs in the dentate gyrus of the hippocampus during adulthood and contributes to sustaining the hippocampal formation. To investigate whether neurogenesis-related pathways are associated with hippocampal volume, we performed gene-set enrichment analysis using summary statistics from a large-scale genome-wide association study (N = 13,163) of hippocampal volume from the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium and two year hippocampal volume changes from baseline in cognitively normal individuals from Alzheimer's Disease Neuroimaging Initiative Cohort (ADNI). Gene-set enrichment analysis of hippocampal volume identified 44 significantly enriched biological pathways (FDR corrected p-value < 0.05), of which 38 pathways were related to neurogenesis-related processes including neurogenesis, generation of new neurons, neuronal development, and neuronal migration and differentiation. For genes highly represented in the significantly enriched neurogenesis-related pathways, gene-based association analysis identified TESC, ACVR1, MSRB3, and DPP4 as significantly associated with hippocampal volume. Furthermore, co-expression network-based functional analysis of gene expression data in the hippocampal subfields, CA1 and CA3, from 32 normal controls showed that distinct co-expression modules were mostly enriched in neurogenesis related pathways. Our results suggest that neurogenesis-related pathways may be enriched for hippocampal volume and that hippocampal volume may serve as a potential phenotype for the investigation of human adult neurogenesis.

Association of Altered Liver Enzymes With Alzheimer Disease Diagnosis, Cognition, Neuroimaging Measures, and Cerebrospinal Fluid Biomarkers

IMPORTANCE

Increasing evidence suggests an important role of liver function in the pathophysiology of Alzheimer disease (AD). The liver is a major metabolic hub; therefore, investigating the association of liver function with AD, cognition, neuroimaging, and CSF biomarkers would improve the understanding of the role of metabolic dysfunction in AD.

OBJECTIVE

To examine whether liver function markers are associated with cognitive dysfunction and the "A/T/N" (amyloid, tau, and neurodegeneration) biomarkers for AD.

DESIGN, SETTING, AND PARTICIPANTS

In this cohort study, serum-based liver function markers were measured from September 1, 2005, to August 31, 2013, in 1581 AD Neuroimaging Initiative participants along with cognitive measures, cerebrospinal fluid (CSF) biomarkers, brain atrophy, brain glucose metabolism, and amyloid-β accumulation. Associations of liver function markers with AD-associated clinical and A/T/N biomarkers were assessed using generalized linear models adjusted for confounding variables and multiple comparisons. Statistical analysis was performed from November 1, 2017, to February 28, 2019.

EXPOSURES

Five serum-based liver function markers (total bilirubin, albumin, alkaline phosphatase, alanine aminotransferase, and aspartate aminotransferase) from AD Neuroimaging Initiative participants were used as exposure variables.

MAIN OUTCOMES AND MEASURES

Primary outcomes included diagnosis of AD, composite scores for executive functioning and memory, CSF biomarkers, atrophy measured by magnetic resonance imaging, brain glucose metabolism measured by fludeoxyglucose F 18 (18F) positron emission tomography, and amyloid-β accumulation measured by [18F]florbetapir positron emission tomography.

RESULTS

Participants in the AD Neuroimaging Initiative (n = 1581; 697 women and 884 men; mean [SD] age, 73.4 [7.2] years) included 407 cognitively normal older adults, 20 with significant memory concern, 298 with early mild cognitive impairment, 544 with late mild cognitive impairment, and 312 with AD. An elevated aspartate aminotransferase (AST) to alanine aminotransferase (ALT) ratio and lower levels of ALT were associated with AD diagnosis (AST to ALT ratio: odds ratio, 7.932 [95% CI, 1.673-37.617]; P = .03; ALT: odds ratio, 0.133 [95% CI, 0.042-0.422]; P = .004) and poor cognitive performance (AST to ALT ratio: β [SE], -0.465 [0.180]; P = .02 for memory composite score; β [SE], -0.679 [0.215]; P = .006 for executive function composite score; ALT: β [SE], 0.397 [0.128]; P = .006 for memory composite score; β [SE], 0.637 [0.152]; P < .001 for executive function composite score). Increased AST to ALT ratio values were associated with lower CSF amyloid-β 1-42 levels (β [SE], -0.170 [0.061]; P = .04) and increased amyloid-β deposition (amyloid biomarkers), higher CSF phosphorylated tau181 (β [SE], 0.175 [0.055]; P = .02) (tau biomarkers) and higher CSF total tau levels (β [SE], 0.160 [0.049]; P = .02) and reduced brain glucose metabolism (β [SE], -0.123 [0.042]; P = .03) (neurodegeneration biomarkers). Lower levels of ALT were associated with increased amyloid-β deposition (amyloid biomarkers), and reduced brain glucose metabolism (β [SE], 0.096 [0.030]; P = .02) and greater atrophy (neurodegeneration biomarkers).

CONCLUSIONS AND RELEVANCE

Consistent associations of serum-based liver function markers with cognitive performance and A/T/N biomarkers for AD highlight the involvement of metabolic disturbances in the pathophysiology of AD. Further studies are needed to determine if these associations represent a causative or secondary role. Liver enzyme involvement in AD opens avenues for novel diagnostics and therapeutics.

Non-linear registration improves statistical power to detect hippocampal atrophy in aging and dementia

OBJECTIVE

To compare the performance of different methods for determining hippocampal atrophy rates using longitudinal MRI scans in aging and Alzheimer's disease (AD).

BACKGROUND

Quantifying hippocampal atrophy caused by neurodegenerative diseases is important to follow the course of the disease. In dementia, the efficacy of new therapies can be partially assessed by measuring their effect on hippocampal atrophy. In radiotherapy, the quantification of radiation-induced hippocampal volume loss is of interest to quantify radiation damage. We evaluated plausibility, reproducibility and sensitivity of eight commonly used methods to determine hippocampal atrophy rates using test-retest scans.

MATERIALS AND METHODS

Manual, FSL-FIRST, FreeSurfer, multi-atlas segmentation (MALF) and non-linear registration methods (Elastix, NiftyReg, ANTs and MIRTK) were used to determine hippocampal atrophy rates on longitudinal T1-weighted MRI from the ADNI database. Appropriate parameters for the non-linear registration methods were determined using a small training dataset (N = 16) in which two-year hippocampal atrophy was measured using test-retest scans of 8 subjects with low and 8 subjects with high atrophy rates. On a larger dataset of 20 controls, 40 mild cognitive impairment (MCI) and 20  AD patients, one-year hippocampal atrophy rates were measured. A repeated measures ANOVA analysis was performed to determine differences between controls, MCI and AD patients. For each method we calculated effect sizes and the required sample sizes to detect one-year volume change between controls and MCI (NCTRL_MCI) and between controls and AD (NCTRL_AD). Finally, reproducibility of hippocampal atrophy rates was assessed using within-session rescans and expressed as an average distance measure DAve, which expresses the difference in atrophy rate, averaged over all subjects. The same DAve was used to determine the agreement between different methods.

RESULTS

Except for MALF, all methods detected a significant group difference between CTRL and AD, but none could find a significant difference between the CTRL and MCI. FreeSurfer and MIRTK required the lowest sample sizes (FreeSurfer: NCTRL_MCI = 115, NCTRL_AD = 17 with DAve = 3.26%; MIRTK: NCTRL_MCI = 97, NCTRL_AD = 11 with DAve = 3.76%), while ANTs was most reproducible (NCTRL_MCI = 162, NCTRL_AD = 37 with DAve = 1.06%), followed by Elastix (NCTRL_MCI = 226, NCTRL_AD = 15 with DAve = 1.78%) and NiftyReg (NCTRL_MCI = 193, NCTRL_AD = 14 with DAve = 2.11%). Manually measured hippocampal atrophy rates required largest sample sizes to detect volume change and were poorly reproduced (NCTRL_MCI = 452, NCTRL_AD = 87 with DAve = 12.39%). Atrophy rates of non-linear registration methods also agreed best with each other.

DISCUSSION AND CONCLUSION

Non-linear registration methods were most consistent in determining hippocampal atrophy and because of their better reproducibility, methods, such as ANTs, Elastix and NiftyReg, are preferred for determining hippocampal atrophy rates on longitudinal MRI. Since performances of non-linear registration methods are well comparable, the preferred method would mostly depend on computational efficiency.

Biomarker-Drug and Liquid Biopsy Co-development for Disease Staging and Targeted Therapy: Cornerstones for Alzheimer's Precision Medicine and Pharmacology

Systems biology studies have demonstrated that different (epi)genetic and pathophysiological alterations may be mapped onto a single tumor’s clinical phenotype thereby revealing commonalities shared by cancers with divergent phenotypes. The success of this approach in cancer based on analyses of traditional and emerging body fluid-based biomarkers has given rise to the concept of liquid biopsy enabling a non-invasive and widely accessible precision medicine approach and a significant paradigm shift in the management of cancer. Serial liquid biopsies offer clues about the evolution of cancer in individual patients across disease stages enabling the application of individualized genetically and biologically guided therapies. Moreover, liquid biopsy is contributing to the transformation of drug research and development strategies as well as supporting clinical practice allowing identification of subsets of patients who may enter pathway-based targeted therapies not dictated by clinical phenotypes alone. A similar liquid biopsy concept is emerging for Alzheimer’s disease, in which blood-based biomarkers adaptable to each patient and stage of disease, may be used for positive and negative patient selection to facilitate establishment of high-value drug targets and counter-measures for drug resistance. Going beyond the “one marker, one drug” model, integrated applications of genomics, transcriptomics, proteomics, receptor expression and receptor cell biology and conformational status assessments during biomarker-drug co-development may lead to a new successful era for Alzheimer’s disease therapeutics. We argue that the time is now for implementing a liquid biopsy-guided strategy for the development of drugs that precisely target Alzheimer’s disease pathophysiology in individual patients.

Altered bile acid profile in mild cognitive impairment and Alzheimer's disease: Relationship to neuroimaging and CSF biomarkers

INTRODUCTION

Bile acids (BAs) are the end products of cholesterol metabolism produced by human and gut microbiome co-metabolism. Recent evidence suggests gut microbiota influence pathological features of Alzheimer's disease (AD) including neuroinflammation and amyloid-β deposition.

METHOD

Serum levels of 20 primary and secondary BA metabolites from the AD Neuroimaging Initiative (n = 1562) were measured using targeted metabolomic profiling. We assessed the association of BAs with the "A/T/N" (amyloid, tau, and neurodegeneration) biomarkers for AD: cerebrospinal fluid (CSF) biomarkers, atrophy (magnetic resonance imaging), and brain glucose metabolism ([18F]FDG PET).

RESULTS

Of 23 BAs and relevant calculated ratios after quality control procedures, three BA signatures were associated with CSF Aβ1-42 ("A") and three with CSF p-tau181 ("T") (corrected P < .05). Furthermore, three, twelve, and fourteen BA signatures were associated with CSF t-tau, glucose metabolism, and atrophy ("N"), respectively (corrected P < .05).

DISCUSSION

This is the first study to show serum-based BA metabolites are associated with "A/T/N" AD biomarkers, providing further support for a role of BA pathways in AD pathophysiology. Prospective clinical observations and validation in model systems are needed to assess causality and specific mechanisms underlying this association.

Identification of exon skipping events associated with Alzheimer's disease in the human hippocampus

BACKGROUND

At least 90% of human genes are alternatively spliced. Alternative splicing has an important function regulating gene expression and miss-splicing can contribute to risk for human diseases, including Alzheimer's disease (AD).

METHODS

We developed a splicing decision model as a molecular mechanism to identify functional exon skipping events and genetic variation affecting alternative splicing on a genome-wide scale by integrating genomics, transcriptomics, and neuroimaging data in a systems biology approach. In this study, we analyzed RNA-Seq data of hippocampus brain tissue from Alzheimer's disease (AD; n = 24) and cognitively normal elderly controls (CN; n = 50) and identified three exon skipping events in two genes (RELN and NOS1) as significantly associated with AD (corrected p-value < 0.05 and fold change > 1.5). Next, we identified single-nucleotide polymorphisms (SNPs) affecting exon skipping events using the splicing decision model and then performed an association analysis of SNPs potentially affecting three exon skipping events with a global cortical measure of amyloid-β deposition measured by [18F] Florbetapir position emission tomography (PET) scan as an AD-related quantitative phenotype. A whole-brain voxel-based analysis was also performed.

RESULTS

Two exons in RELN and one exon in NOS1 showed significantly lower expression levels in the AD participants compared to CN participants, suggesting that the exons tend to be skipped more in AD. We also showed the loss of the core protein structure due to the skipped exons using the protein 3D structure analysis. The targeted SNP-based association analysis identified one intronic SNP (rs362771) adjacent to the skipped exon 24 in RELN as significantly associated with cortical amyloid-β levels (corrected p-value < 0.05). This SNP is within the splicing regulatory element, i.e., intronic splicing enhancer. The minor allele of rs362771 conferred decreases in cortical amyloid-β levels in the right temporal and bilateral parietal lobes.

CONCLUSIONS

Our results suggest that exon skipping events and splicing-affecting SNPs in the human hippocampus may contribute to AD pathogenesis. Integration of multiple omics and neuroimaging data provides insights into possible mechanisms underlying AD pathophysiology through exon skipping and may help identify novel therapeutic targets.

Early Life Stress and Epigenetics in Late-onset Alzheimer's Dementia: A Systematic Review

Involvement of life stress in Late-Onset Alzheimer's Disease (LOAD) has been evinced in longitudinal cohort epidemiological studies, and endocrinologic evidence suggests involvements of catecholamine and corticosteroid systems in LOAD. Early Life Stress (ELS) rodent models have successfully demonstrated sequelae of maternal separation resulting in LOAD-analogous pathology, thereby supporting a role of insulin receptor signalling pertaining to GSK-3beta facilitated tau hyper-phosphorylation and amyloidogenic processing. Discussed are relevant ELS studies, and findings from three mitogen-activated protein kinase pathways (JNK/SAPK pathway, ERK pathway, p38/MAPK pathway) relevant for mediating environmental stresses. Further considered were the roles of autophagy impairment, neuroinflammation, and brain insulin resistance. For the meta-analytic evaluation, 224 candidate gene loci were extracted from reviews of animal studies of LOAD pathophysiological mechanisms, of which 60 had no positive results in human LOAD association studies. These loci were combined with 89 gene loci confirmed as LOAD risk genes in previous GWAS and WES. Of the 313 risk gene loci evaluated, there were 35 human reports on epigenomic modifications in terms of methylation or histone acetylation. 64 microRNA gene regulation mechanisms were published for the compiled loci. Genomic association studies support close relations of both noradrenergic and glucocorticoid systems with LOAD. For HPA involvement, a CRHR1 haplotype with MAPT was described, but further association of only HSD11B1 with LOAD found; however, association of FKBP1 and NC3R1 polymorphisms was documented in support of stress influence to LOAD. In the brain insulin system, IGF2R, INSR, INSRR, and plasticity regulator ARC, were associated with LOAD. Pertaining to compromised myelin stability in LOAD, relevant associations were found for BIN1, RELN, SORL1, SORCS1, CNP, MAG, and MOG. Regarding epigenetic modifications, both methylation variability and de-acetylation were reported for LOAD. The majority of up-to-date epigenomic findings include reported modifications in the well-known LOAD core pathology loci MAPT, BACE1, APP (with FOS, EGR1), PSEN1, PSEN2, and highlight a central role of BDNF. Pertaining to ELS, relevant loci are FKBP5, EGR1, GSK3B; critical roles of inflammation are indicated by CRP, TNFA, NFKB1 modifications; for cholesterol biosynthesis, DHCR24; for myelin stability BIN1, SORL1, CNP; pertaining to (epi)genetic mechanisms, hTERT, MBD2, DNMT1, MTHFR2. Findings on gene regulation were accumulated for BACE1, MAPK signalling, TLR4, BDNF, insulin signalling, with most reports for miR-132 and miR-27. Unclear in epigenomic studies remains the role of noradrenergic signalling, previously demonstrated by neuropathological findings of childhood nucleus caeruleus degeneration for LOAD tauopathy.

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.

[A rare variant in the sortilin-related receptor 1 gene is associated with declined cognitive functions in the elderly]

AIM

To estimate the association of rs11218343 in the sortilin-related receptor 1 (SORL1) gene with cognitive performance in the elderly and with Alzheimer's disease (AD) in the Russian population.

MATERIAL AND METHODS

A sample included 586 elderly people (mean age 70.9±5.7 years) without AD diagnosis and 100 patients with late-onset AD (mean age 72.1±7.8 years) from the Tomsk population. SORL1 rs11218343 was genotyped using PCR and MALDI-TOF mass spectrometry. Cognitive performance in the sample of elderly without AD was assessed by Montreal Cognitive Assessment (MoCA) test.

RESULTS

Allele frequencies of the SORL1 polymorphism were not significantly different between the elderly without AD and AD patients. However mean MoCA score in the carriers of the rare allele (19.00±6.61) was significantly lower than in homozygotes for the common variant (22.25±3.89) (F=4.97; p=0.026).

CONCLUSION

The rare variant in SORL1 gene previously associated with AD in genome-wide association studies and meta-analyses was associated with lower total МоСА scores in the random sample of elderly people that suggests declined cognitive functions in the carriers of this variant in elderly.

Genetic variation affecting exon skipping contributes to brain structural atrophy in Alzheimer's disease

Genetic variation in cis-regulatory elements related to splicing machinery and splicing regulatory elements (SREs) results in exon skipping and undesired protein products. We developed a splicing decision model to identify actionable loci among common SNPs for gene regulation. The splicing decision model identified SNPs affecting exon skipping by analyzing sequence-driven alternative splicing (AS) models and by scanning the genome for the regions with putative SRE motifs. We used non-Hispanic Caucasians with neuroimaging, and fluid biomarkers for Alzheimer's disease (AD) and identified 17,088 common exonic SNPs affecting exon skipping. GWAS identified one SNP (rs1140317) in HLA-DQB1 as significantly associated with entorhinal cortical thickness, AD neuroimaging biomarker, after controlling for multiple testing. Further analysis revealed that rs1140317 was significantly associated with brain amyloid-f deposition (PET and CSF). HLA-DQB1 is an essential immune gene and may regulate AS, thereby contributing to AD pathology. SRE may hold potential as novel therapeutic targets for AD.

Genome-wide association study of Alzheimer's disease endophenotypes at prediagnosis stages

INTRODUCTION

Genetic associations for endophenotypes of Alzheimer's disease (AD) in cognitive stages preceding AD have not been thoroughly evaluated.

METHODS

We conducted genome-wide association studies for AD-related endophenotypes including hippocampal volume, logical memory scores, and cerebrospinal fluid Aβ42 and total/phosphorylated tau in cognitively normal (CN), mild cognitive impairment, and AD dementia subjects from the Alzheimer's Disease Neuroimaging Initiative study.

RESULTS

In CN subjects, study-wide significant (P < 8.3 × 10-9) loci were identified for total tau near SRRM4 and C14orf79 and for hippocampal volume near MTUS1. In mild cognitive impairment subjects, study-wide significant association was found with single nucleotide polymorphisms (SNPs) near ZNF804B for logical memory test of delayed recall scores. We found consistent expression patterns of C14orf40 and MTUS1 in carriers with risk alleles of expression SNPs and in brains of AD patients, compared with in the noncarriers and in brains of controls.

DISCUSSION

Our findings for AD-related brain changes before AD provide insight about early AD-related biological processes.

Analysis of Association of Genetic Markers in the LUZP2 and FBXO40 Genes with the Normal Variability in Cognitive Performance in the Elderly

Cognitive performance is an important endophenotype for various neurodegenerative and neuropsychiatric traits. In the present study two genetic variants in the leucine-zipper protein (LUZP2) and the F-box 40 protein (FBXO40) genes, previously reported to be genome-wide significant for Alzheimer's diseases and schizophrenia, were examined for an association with cognitive abilities in normal elderly from the Russian population. Rs1021261 in the LUZP2 and rs3772130 in the FBXO40 were genotyped by multiplex PCR and MALDI-TOF mass spectrometry in a sample of 708 normal elderly subjects tested for cognitive performance using the Montreal Cognitive Assessment (MoCA). Association of genetic variability with the MoCA scores was estimated by parametric and nonparametric analysis of variance and by the frequency comparison between upper and lower quartiles of MoCA distribution. Significantly higher frequency of "TT" genotype of rs1021261 in the LUZP2 gene as well as "A" allele and "AA" genotype of rs3772130 in the FBXO40 gene was found in a subsample of individuals with the MoCA score less than 20 comparing to the fourth quartile's subsample (MoCA > 25). The data of the present study suggests that genetic variability in the LUZP2 and FBXO40 loci associated with neurodegenerative and neuropsychiatric diseases is also contributed to the normal variability in cognitive performance in the elderly.

Associations of the Top 20 Alzheimer Disease Risk Variants With Brain Amyloidosis

Importance

Late-onset Alzheimer disease (AD) is highly heritable. Genome-wide association studies have identified more than 20 AD risk genes. The precise mechanism through which many of these genes are associated with AD remains unknown.

Objective

To investigate the association of the top 20 AD risk variants with brain amyloidosis.

Design, Setting, and Participants

This study analyzed the genetic and florbetapir F 18 data from 322 cognitively normal control individuals, 496 individuals with mild cognitive impairment, and 159 individuals with AD dementia who had genome-wide association studies and 18F-florbetapir positron emission tomographic data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), a prospective, observational, multisite tertiary center clinical and biomarker study. This ongoing study began in 2005.

Main Outcomes and Measures

The study tested the association of AD risk allele carrier status (exposure) with florbetapir mean standard uptake value ratio (outcome) using stepwise multivariable linear regression while controlling for age, sex, and apolipoprotein E ε4 genotype. The study also reports on an exploratory 3-dimensional stepwise regression model using an unbiased voxelwise approach in Statistical Parametric Mapping 8 with cluster and significance thresholds at 50 voxels and uncorrected P < .01.

Results

This study included 977 participants (mean [SD] age, 74 [7.5] years; 535 [54.8%] male and 442 [45.2%] female) from the ADNI-1, ADNI-2, and ADNI-Grand Opportunity. The adenosine triphosphate-binding cassette subfamily A member 7 (ABCA7) gene had the strongest association with amyloid deposition (χ2 = 8.38, false discovery rate-corrected P < .001), after apolioprotein E ε4. Significant associations were found between ABCA7 in the asymptomatic and early symptomatic disease stages, suggesting an association with rapid amyloid accumulation. The fermitin family homolog 2 (FERMT2) gene had a stage-dependent association with brain amyloidosis (FERMT2 × diagnosis χ2 = 3.53, false discovery rate-corrected P = .05), which was most pronounced in the mild cognitive impairment stage.

Conclusions and Relevance

This study found an association of several AD risk variants with brain amyloidosis. The data also suggest that AD genes might differentially regulate AD pathologic findings across the disease stages.

Targeted neurogenesis pathway-based gene analysis identifies ADORA2A associated with hippocampal volume in mild cognitive impairment and Alzheimer's disease

Alzheimer's disease (AD) patients display hippocampal atrophy, memory impairment, and cognitive decline. New neurons are generated throughout adulthood in 2 regions of the brain implicated in AD, the dentate gyrus of the hippocampus and the subventricular zone of the olfactory bulb. Disruption of this process contributes to neurodegenerative diseases including AD, and many of the molecular players in AD are also modulators of adult neurogenesis. However, the genetic mechanisms underlying adult neurogenesis in AD have been underexplored. To address this gap, we performed a gene-based association analysis in cognitively normal and impaired participants using neurogenesis pathway-related candidate genes curated from existing databases, literature mining, and large-scale genome-wide association study findings. A gene-based association analysis identified adenosine A2a receptor (ADORA2A) as significantly associated with hippocampal volume and the association between rs9608282 within ADORA2A and hippocampal volume was replicated in the meta-analysis after multiple comparison adjustments (p = 7.88 × 10-6). The minor allele of rs9608282 in ADORA2A is associated with larger hippocampal volumes and better memory.

Pattern Discovery in Brain Imaging Genetics via SCCA Modeling with a Generic Non-convex Penalty

Brain imaging genetics intends to uncover associations between genetic markers and neuroimaging quantitative traits. Sparse canonical correlation analysis (SCCA) can discover bi-multivariate associations and select relevant features, and is becoming popular in imaging genetic studies. The L1-norm function is not only convex, but also singular at the origin, which is a necessary condition for sparsity. Thus most SCCA methods impose [Formula: see text]-norm onto the individual feature or the structure level of features to pursuit corresponding sparsity. However, the [Formula: see text]-norm penalty over-penalizes large coefficients and may incurs estimation bias. A number of non-convex penalties are proposed to reduce the estimation bias in regression tasks. But using them in SCCA remains largely unexplored. In this paper, we design a unified non-convex SCCA model, based on seven non-convex functions, for unbiased estimation and stable feature selection simultaneously. We also propose an efficient optimization algorithm. The proposed method obtains both higher correlation coefficients and better canonical loading patterns. Specifically, these SCCA methods with non-convex penalties discover a strong association between the APOE e4 rs429358 SNP and the hippocampus region of the brain. They both are Alzheimer's disease related biomarkers, indicating the potential and power of the non-convex methods in brain imaging genetics.

Association analysis of rare variants near the APOE region with CSF and neuroimaging biomarkers of Alzheimer's disease

BACKGROUND

The APOE ε4 allele is the most significant common genetic risk factor for late-onset Alzheimer's disease (LOAD). The region surrounding APOE on chromosome 19 has also shown consistent association with LOAD. However, no common variants in the region remain significant after adjusting for APOE genotype. We report a rare variant association analysis of genes in the vicinity of APOE with cerebrospinal fluid (CSF) and neuroimaging biomarkers of LOAD.

METHODS

Whole genome sequencing (WGS) was performed on 817 blood DNA samples from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Sequence data from 757 non-Hispanic Caucasian participants was used in the present analysis. We extracted all rare variants (MAF (minor allele frequency) < 0.05) within a 312 kb window in APOE's vicinity encompassing 12 genes. We assessed CSF and neuroimaging (MRI and PET) biomarkers as LOAD-related quantitative endophenotypes. Gene-based analyses of rare variants were performed using the optimal Sequence Kernel Association Test (SKAT-O).

RESULTS

A total of 3,334 rare variants (MAF < 0.05) were found within the APOE region. Among them, 72 rare non-synonymous variants were observed. Eight genes spanning the APOE region were significantly associated with CSF Aβ_1-42 (p < 1.0 × 10^-3). After controlling for APOE genotype and adjusting for multiple comparisons, 4 genes (CBLC, BCAM, APOE, and RELB) remained significant. Whole-brain surface-based analysis identified highly significant clusters associated with rare variants of CBLC in the temporal lobe region including the entorhinal cortex, as well as frontal lobe regions. Whole-brain voxel-wise analysis of amyloid PET identified significant clusters in the bilateral frontal and parietal lobes showing associations of rare variants of RELB with cortical amyloid burden.

CONCLUSIONS

Rare variants within genes spanning the APOE region are significantly associated with LOAD-related CSF Aβ_1-42 and neuroimaging biomarkers after adjusting for APOE genotype. These findings warrant further investigation and illustrate the role of next generation sequencing and quantitative endophenotypes in assessing rare variants which may help explain missing heritability in AD and other complex diseases.

Hippocampal Sclerosis of Aging, a Common Alzheimer's Disease 'Mimic': Risk Genotypes are Associated with Brain Atrophy Outside the Temporal Lobe

Hippocampal sclerosis of aging (HS-Aging) is a common brain disease in older adults with a clinical course that is similar to Alzheimer's disease. Four single-nucleotide polymorphisms (SNPs) have previously shown association with HS-Aging. The present study investigated structural brain changes associated with these SNPs using surface-based analysis. Participants from the Alzheimer's Disease Neuroimaging Initiative cohort (ADNI; n = 1,239), with both MRI scans and genotype data, were used to assess the association between brain atrophy and previously identified HS-Aging risk SNPs in the following genes: GRN, TMEM106B, ABCC9, and KCNMB2 (minor allele frequency for each is >30%). A fifth SNP (near the ABCC9 gene) was evaluated in post-hoc analysis. The GRN risk SNP (rs5848_T) was associated with a pattern of atrophy in the dorsomedial frontal lobes bilaterally, remarkable since GRN is a risk factor for frontotemporal dementia. The ABCC9 risk SNP (rs704180_A) was associated with multifocal atrophy whereas a SNP (rs7488080_A) nearby (∼50 kb upstream) ABCC9 was associated with atrophy in the right entorhinal cortex. Neither TMEM106B (rs1990622_T), KCNMB2 (rs9637454_A), nor any of the non-risk alleles were associated with brain atrophy. When all four previously identified HS-Aging risk SNPs were summed into a polygenic risk score, there was a pattern of associated multifocal brain atrophy in a predominately frontal pattern. We conclude that common SNPs previously linked to HS-Aging pathology were associated with a distinct pattern of anterior cortical atrophy. Genetic variation associated with HS-Aging pathology may represent a non-Alzheimer's disease contribution to atrophy outside of the hippocampus in older adults.

Genomics and CSF analyses implicate thyroid hormone in hippocampal sclerosis of aging

We report evidence of a novel pathogenetic mechanism in which thyroid hormone dysregulation contributes to dementia in elderly persons. Two single nucleotide polymorphisms (SNPs) on chromosome 12p12 were the initial foci of our study: rs704180 and rs73069071. These SNPs were identified by separate research groups as risk alleles for non-Alzheimer's neurodegeneration. We found that the rs73069071 risk genotype was associated with hippocampal sclerosis (HS) pathology among people with the rs704180 risk genotype (National Alzheimer's Coordinating Center/Alzheimer's Disease Genetic Consortium data; n = 2113, including 241 autopsy-confirmed HS cases). Furthermore, both rs704180 and rs73069071 risk genotypes were associated with widespread brain atrophy visualized by MRI (Alzheimer's Disease Neuroimaging Initiative data; n = 1239). In human brain samples from the Braineac database, both rs704180 and rs73069071 risk genotypes were associated with variation in expression of ABCC9, a gene which encodes a metabolic sensor protein in astrocytes. The rs73069071 risk genotype was also associated with altered expression of a nearby astrocyte-expressed gene, SLCO1C1. Analyses of human brain gene expression databases indicated that the chromosome 12p12 locus may regulate particular astrocyte-expressed genes induced by the active form of thyroid hormone, triiodothyronine (T3). This is informative biologically, because the SLCO1C1 protein transports thyroid hormone into astrocytes from blood. Guided by the genomic data, we tested the hypothesis that altered thyroid hormone levels could be detected in cerebrospinal fluid (CSF) obtained from persons with HS pathology. Total T3 levels in CSF were elevated in HS cases (p < 0.04 in two separately analyzed groups), but not in Alzheimer's disease cases, relative to controls. No change was detected in the serum levels of thyroid hormone (T3 or T4) in a subsample of HS cases prior to death. We conclude that brain thyroid hormone perturbation is a potential pathogenetic factor in HS that may also provide the basis for a novel CSF-based clinical biomarker.

Genetic Influences on Plasma Homocysteine Levels in African Americans and Yoruba Nigerians

Plasma homocysteine, a metabolite involved in key cellular methylation processes seems to be implicated in cognitive functions and cardiovascular health with its high levels representing a potential modifiable risk factor for Alzheimer's disease (AD) and other dementias. A better understanding of the genetic factors regulating homocysteine levels, particularly in non-white populations, may help in risk stratification analyses of existing clinical trials and may point to novel targets for homocysteine-lowering therapy. To identify genetic influences on plasma homocysteine levels in individuals with African ancestry, we performed a targeted gene and pathway-based analysis using a priori biological information and then to identify new association performed a genome-wide association study. All analyses used combined data from the African American and Yoruba cohorts from the Indianapolis-Ibadan Dementia Project. Targeted analyses demonstrated significant associations of homocysteine and variants within the CBS (Cystathionine beta-Synthase) gene. We identified a novel genome-wide significant association of the AD risk gene CD2AP (CD2-associated protein) with plasma homocysteine levels in both cohorts. Minor allele (T) carriers of identified CD2AP variant (rs6940729) exhibited decreased homocysteine level. Pathway enrichment analysis identified several interesting pathways including the GABA receptor activation pathway. This is noteworthy given the known antagonistic effect of homocysteine on GABA receptors. These findings identify several new targets warranting further investigation in relation to the role of homocysteine in neurodegeneration.

Association of DNA Methylation Differences With Schizophrenia in an Epigenome-Wide Association Study

IMPORTANCE

DNA methylation may play an important role in schizophrenia (SZ), either directly as a mechanism of pathogenesis or as a biomarker of risk.

OBJECTIVE

To scan genome-wide DNA methylation data to identify differentially methylated CpGs between SZ cases and controls.

DESIGN, SETTING, AND PARTICIPANTS

Epigenome-wide association study begun in 2008 using DNA methylation levels of 456 513 CpG loci measured on the Infinium HumanMethylation450 array (Illumina) in a consortium of case-control studies for initial discovery and in an independent replication set. Primary analyses used general linear regression, adjusting for age, sex, race/ethnicity, smoking, batch, and cell type heterogeneity. The discovery set contained 689 SZ cases and 645 controls (n = 1334), from 3 multisite consortia: the Consortium on the Genetics of Endophenotypes in Schizophrenia, the Project among African-Americans To Explore Risks for Schizophrenia, and the Multiplex Multigenerational Family Study of Schizophrenia. The replication set contained 247 SZ cases and 250 controls (n = 497) from the Genomic Psychiatry Cohort.

MAIN OUTCOMES AND MEASURES

Identification of differentially methylated positions across the genome in SZ cases compared with controls.

RESULTS

Of the 689 case participants in the discovery set, 477 (69%) were men and 258 (37%) were non-African American; of the 645 controls, 273 (42%) were men and 419 (65%) were non-African American. In our replication set, cases/controls were 76% male and 100% non-African American. We identified SZ-associated methylation differences at 923 CpGs in the discovery set (false discovery rate, <0.2). Of these, 625 showed changes in the same direction including 172 with P < .05 in the replication set. Some replicated differentially methylated positions are located in a top-ranked SZ region from genome-wide association study analyses.

CONCLUSIONS AND RELEVANCE

This analysis identified 172 replicated new associations with SZ after careful correction for cell type heterogeneity and other potential confounders. The overlap with previous genome-wide association study data can provide potential insights into the functional relevance of genetic signals for SZ.