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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 [ 18 F] 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.

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., (Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

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., (Copyright © 2017 Elsevier Inc. All rights reserved.)

The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (r g =-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness.

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.

Memory impairment is the cardinal early feature of Alzheimer's disease, a highly prevalent disorder whose causes remain only partially understood. To identify novel genetic predictors, we used an integrative genomics approach to perform the largest study to date of human memory (n=14 781). Using a genome-wide screen, we discovered a novel association of a polymorphism in the pro-apoptotic gene FASTKD2 (fas-activated serine/threonine kinase domains 2; rs7594645-G) with better memory performance and replicated this finding in independent samples. Consistent with a neuroprotective effect, rs7594645-G carriers exhibited increased hippocampal volume and gray matter density and decreased cerebrospinal fluid levels of apoptotic mediators. The MTOR (mechanistic target of rapamycin) gene and pathways related to endocytosis, cholinergic neurotransmission, epidermal growth factor receptor signaling and immune regulation, among others, also displayed association with memory. These findings nominate FASTKD2 as a target for modulating neurodegeneration and suggest potential mechanisms for therapies to combat memory loss in normal cognitive aging and dementia.

We used whole-exome sequencing to identify variants other than APOE associated with the rate of hippocampal atrophy in amnestic mild cognitive impairment. An in-silico predicted missense variant in REST (rs3796529) was found exclusively in subjects with slow hippocampal volume loss and validated using unbiased whole-brain analysis and meta-analysis across 5 independent cohorts. REST is a master regulator of neurogenesis and neuronal differentiation that has not been previously implicated in Alzheimer's disease. These findings nominate REST and its functional pathways as protective and illustrate the potential of combining next-generation sequencing with neuroimaging to discover novel disease mechanisms and potential therapeutic targets., (© 2015 American Neurological Association.)

Whole-exome sequencing of individuals with mild cognitive impairment, combined with genotype imputation, was used to identify coding variants other than the apolipoprotein E (APOE) ε4 allele associated with rate of hippocampal volume loss using an extreme trait design. Matched unrelated APOE ε3 homozygous male Caucasian participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were selected at the extremes of the 2-year longitudinal change distribution of hippocampal volume (eight subjects with rapid rates of atrophy and eight with slow/stable rates of atrophy). We identified 57 non-synonymous single nucleotide variants (SNVs) which were found exclusively in at least 4 of 8 subjects in the rapid atrophy group, but not in any of the 8 subjects in the slow atrophy group. Among these SNVs, the variants that accounted for the greatest group difference and were predicted in silico as 'probably damaging' missense variants were rs9610775 (CARD10) and rs1136410 (PARP1). To further investigate and extend the exome findings in a larger sample, we conducted quantitative trait analysis including whole-brain search in the remaining ADNI APOE ε3/ε3 group (N=315). Genetic variation within PARP1 and CARD10 was associated with rate of hippocampal neurodegeneration in APOE ε3/ε3. Meta-analysis across five independent cross sectional cohorts indicated that rs1136410 is also significantly associated with hippocampal volume in APOE ε3/ε3 individuals (N=923). Larger sequencing studies and longitudinal follow-up are needed for confirmation. The combination of next-generation sequencing and quantitative imaging phenotypes holds significant promise for discovery of variants involved in neurodegeneration.

Identifying genetic variants influencing human brain structures may reveal new biological mechanisms underlying cognition and neuropsychiatric illness. The volume of the hippocampus is a biomarker of incipient Alzheimer's disease and is reduced in schizophrenia, major depression and mesial temporal lobe epilepsy. Whereas many brain imaging phenotypes are highly heritable, identifying and replicating genetic influences has been difficult, as small effects and the high costs of magnetic resonance imaging (MRI) have led to underpowered studies. Here we report genome-wide association meta-analyses and replication for mean bilateral hippocampal, total brain and intracranial volumes from a large multinational consortium. The intergenic variant rs7294919 was associated with hippocampal volume (12q24.22; N = 21,151; P = 6.70 × 10(-16)) and the expression levels of the positional candidate gene TESC in brain tissue. Additionally, rs10784502, located within HMGA2, was associated with intracranial volume (12q14.3; N = 15,782; P = 1.12 × 10(-12)). We also identified a suggestive association with total brain volume at rs10494373 within DDR2 (1q23.3; N = 6,500; P = 5.81 × 10(-7)).

Genetic mapping of hippocampal shape, an under-explored area, has strong potential as a neurodegeneration biomarker for AD and MCI. This study investigates the genetic effects of top candidate single nucleotide polymorphisms (SNPs) on hippocampal shape features as quantitative traits (QTs) in a large cohort. FS+LDDMM was used to segment hippocampal surfaces from MRI scans and shape features were extracted after surface registration. Elastic net (EN) and sparse canonical correlation analysis (SCCA) were proposed to examine SNP-QT associations, and compared with multiple regression (MR). Although similar in power, EN yielded substantially fewer predictors than MR. Detailed surface mapping of global and localized genetic effects were identified by MR and EN to reveal multi-SNP-single-QT relationships, and by SCCA to discover multi-SNP-multi-QT associations. Shape analysis identified stronger SNP-QT correlations than volume analysis. Sparse multivariate models have greater power to reveal complex SNP-QT relationships. Genetic analysis of quantitative shape features has considerable potential for enhancing mechanistic understanding of complex disorders like AD.