Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease

Preclinical Alzheimer's disease: Definition, natural history, and diagnostic criteria

During the past decade, a conceptual shift occurred in the field of Alzheimer's disease (AD) considering the disease as a continuum. Thanks to evolving biomarker research and substantial discoveries, it is now possible to identify the disease even at the preclinical stage before the occurrence of the first clinical symptoms. This preclinical stage of AD has become a major research focus as the field postulates that early intervention may offer the best chance of therapeutic success. To date, very little evidence is established on this "silent" stage of the disease. A clarification is needed about the definitions and lexicon, the limits, the natural history, the markers of progression, and the ethical consequence of detecting the disease at this asymptomatic stage. This article is aimed at addressing all the different issues by providing for each of them an updated review of the literature and evidence, with practical recommendations.

Global and local ancestry in African-Americans: Implications for Alzheimer's disease risk

INTRODUCTION

African-American (AA) individuals have a higher risk for late-onset Alzheimer's disease (LOAD) than Americans of primarily European ancestry (EA). Recently, the largest genome-wide association study in AAs to date confirmed that six of the Alzheimer's disease (AD)-related genetic variants originally discovered in EA cohorts are also risk variants in AA; however, the risk attributable to many of the loci (e.g., APOE, ABCA7) differed substantially from previous studies in EA. There likely are risk variants of higher frequency in AAs that have not been discovered.

METHODS

We performed a comprehensive analysis of genetically determined local and global ancestry in AAs with regard to LOAD status.

RESULTS

Compared to controls, LOAD cases showed higher levels of African ancestry, both globally and at several LOAD relevant loci, which explained risk for AD beyond global differences.

DISCUSSION

Exploratory post hoc analyses highlight regions with greatest differences in ancestry as potential candidate regions for future genetic analyses.

Mitochondrial lysates induce inflammation and Alzheimer's disease-relevant changes in microglial and neuronal cells

Neuroinflammation occurs in Alzheimer's disease (AD). While AD genetic studies implicate inflammation-relevant genes and fibrillar amyloid-β protein promotes inflammation, our understanding of AD neuroinflammation nevertheless remains incomplete. In this study we hypothesized damage-associated molecular pattern (DAMP) molecules arising from mitochondria, intracellular organelles that resemble bacteria, could contribute to AD neuroinflammation. To preliminarily test this possibility, we exposed neuronal and microglial cell lines to enriched mitochondrial lysates. BV2 microglial cells treated with mitochondrial lysates showed decreased TREM2 mRNA, increased TNFα mRNA, increased MMP-8 mRNA, increased IL-8 mRNA, redistribution of NFκB to the nucleus, and increased p38 MAPK phosphorylation. SH-SY5Y neuronal cells treated with mitochondrial lysates showed increased TNFα mRNA, increased NFκB protein, decreased IκBα protein, increased AβPP mRNA, and increased AβPP protein. Enriched mitochondrial lysates from SH-SY5Y cells lacking detectable mitochondrial DNA (ρ0 cells) failed to induce any of these changes, while mtDNA obtained directly from mitochondria (but not PCR-amplified mtDNA) increased BV2 cell TNFα mRNA. These results indicate at least one mitochondrial-derived DAMP molecule, mtDNA, can induce inflammatory changes in microglial and neuronal cell lines. Our data are consistent with the hypothesis that a mitochondrial-derived DAMP molecule or molecules could contribute to AD neuroinflammation.

Alzheimer's disease risk variants modulate endophenotypes in mild cognitive impairment

INTRODUCTION

We evaluated the effect of Alzheimer's disease (AD) susceptibility loci on endophenotypes closely related with AD pathology in patients with mild cognitive impairment (MCI).

METHODS

We selected 1730 MCI patients from four independent data sets. Weighted polygenic risk scores (PGS) were constructed of 18 non-apolipoprotein E (APOE) AD risk variants. In addition, we determined APOE genotype. AD endophenotypes were cognitive decline over time and cerebrospinal fluid (CSF) biomarkers (aβ, tau, ptau).

RESULTS

PGS was modestly associated with cognitive decline over time, as measured by mini-mental state examination (MMSE) (β ± SE:-0.24 ± 0.10; P = .012), and with CSF levels of tau and ptau (tau: 1.38 ± 0.36, P = 1.21 × 10(-4); ptau: 1.40 ± 0.36, P = 1.02 × 10(-4)).

DISCUSSION

In MCI, we observed a joint effect of AD susceptibility loci on nonamyloid endophenotypes, suggesting a link of these genetic loci with neuronal degeneration in general rather than with Alzheimer-related amyloid deposition.

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

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

Novel loci and pathways significantly associated with longevity

Only two genome-wide significant loci associated with longevity have been identified so far, probably because of insufficient sample sizes of centenarians, whose genomes may harbor genetic variants associated with health and longevity. Here we report a genome-wide association study (GWAS) of Han Chinese with a sample size 2.7 times the largest previously published GWAS on centenarians. We identified 11 independent loci associated with longevity replicated in Southern-Northern regions of China, including two novel loci (rs2069837-IL6; rs2440012-ANKRD20A9P) with genome-wide significance and the rest with suggestive significance (P < 3.65 × 10(-5)). Eight independent SNPs overlapped across Han Chinese, European and U.S. populations, and APOE and 5q33.3 were replicated as longevity loci. Integrated analysis indicates four pathways (starch, sucrose and xenobiotic metabolism; immune response and inflammation; MAPK; calcium signaling) highly associated with longevity (P ≤ 0.006) in Han Chinese. The association with longevity of three of these four pathways (MAPK; immunity; calcium signaling) is supported by findings in other human cohorts. Our novel finding on the association of starch, sucrose and xenobiotic metabolism pathway with longevity is consistent with the previous results from Drosophilia. This study suggests protective mechanisms including immunity and nutrient metabolism and their interactions with environmental stress play key roles in human longevity.

HYDRA: Revealing heterogeneity of imaging and genetic patterns through a multiple max-margin discriminative analysis framework

Multivariate pattern analysis techniques have been increasingly used over the past decade to derive highly sensitive and specific biomarkers of diseases on an individual basis. The driving assumption behind the vast majority of the existing methodologies is that a single imaging pattern can distinguish between healthy and diseased populations, or between two subgroups of patients (e.g., progressors vs. non-progressors). This assumption effectively ignores the ample evidence for the heterogeneous nature of brain diseases. Neurodegenerative, neuropsychiatric and neurodevelopmental disorders are largely characterized by high clinical heterogeneity, which likely stems in part from underlying neuroanatomical heterogeneity of various pathologies. Detecting and characterizing heterogeneity may deepen our understanding of disease mechanisms and lead to patient-specific treatments. However, few approaches tackle disease subtype discovery in a principled machine learning framework. To address this challenge, we present a novel non-linear learning algorithm for simultaneous binary classification and subtype identification, termed HYDRA (Heterogeneity through Discriminative Analysis). Neuroanatomical subtypes are effectively captured by multiple linear hyperplanes, which form a convex polytope that separates two groups (e.g., healthy controls from pathologic samples); each face of this polytope effectively defines a disease subtype. We validated HYDRA on simulated and clinical data. In the latter case, we applied the proposed method independently to the imaging and genetic datasets of the Alzheimer's Disease Neuroimaging Initiative (ADNI 1) study. The imaging dataset consisted of T1-weighted volumetric magnetic resonance images of 123 AD patients and 177 controls. The genetic dataset consisted of single nucleotide polymorphism information of 103 AD patients and 139 controls. We identified 3 reproducible subtypes of atrophy in AD relative to controls: (1) diffuse and extensive atrophy, (2) precuneus and extensive temporal lobe atrophy, as well some prefrontal atrophy, (3) atrophy pattern very much confined to the hippocampus and the medial temporal lobe. The genetics dataset yielded two subtypes of AD characterized mainly by the presence/absence of the apolipoprotein E (APOE) ε4 genotype, but also involving differential presence of risk alleles of CD2AP, SPON1 and LOC39095 SNPs that were associated with differences in the respective patterns of brain atrophy, especially in the precuneus. The results demonstrate the potential of the proposed approach to map disease heterogeneity in neuroimaging and genetic studies.

Predicting Progression from Mild Cognitive Impairment to Alzheimer's Dementia Using Clinical, MRI, and Plasma Biomarkers via Probabilistic Pattern Classification

Background

Individuals with mild cognitive impairment (MCI) have a substantially increased risk of developing dementia due to Alzheimer's disease (AD). In this study, we developed a multivariate prognostic model for predicting MCI-to-dementia progression at the individual patient level.

Methods

Using baseline data from 259 MCI patients and a probabilistic, kernel-based pattern classification approach, we trained a classifier to distinguish between patients who progressed to AD-type dementia (n = 139) and those who did not (n = 120) during a three-year follow-up period. More than 750 variables across four data sources were considered as potential predictors of progression. These data sources included risk factors, cognitive and functional assessments, structural magnetic resonance imaging (MRI) data, and plasma proteomic data. Predictive utility was assessed using a rigorous cross-validation framework.

Results

Cognitive and functional markers were most predictive of progression, while plasma proteomic markers had limited predictive utility. The best performing model incorporated a combination of cognitive/functional markers and morphometric MRI measures and predicted progression with 80% accuracy (83% sensitivity, 76% specificity, AUC = 0.87). Predictors of progression included scores on the Alzheimer's Disease Assessment Scale, Rey Auditory Verbal Learning Test, and Functional Activities Questionnaire, as well as volume/cortical thickness of three brain regions (left hippocampus, middle temporal gyrus, and inferior parietal cortex). Calibration analysis revealed that the model is capable of generating probabilistic predictions that reliably reflect the actual risk of progression. Finally, we found that the predictive accuracy of the model varied with patient demographic, genetic, and clinical characteristics and could be further improved by taking into account the confidence of the predictions.

Conclusions

We developed an accurate prognostic model for predicting MCI-to-dementia progression over a three-year period. The model utilizes widely available, cost-effective, non-invasive markers and can be used to improve patient selection in clinical trials and identify high-risk MCI patients for early treatment.

Chronic consumption of a western diet induces robust glial activation in aging mice and in a mouse model of Alzheimer's disease

Studies have assessed individual components of a western diet, but no study has assessed the long-term, cumulative effects of a western diet on aging and Alzheimer's disease (AD). Therefore, we have formulated the first western-style diet that mimics the fat, carbohydrate, protein, vitamin and mineral levels of western diets. This diet was fed to aging C57BL/6J (B6) mice to identify phenotypes that may increase susceptibility to AD, and to APP/PS1 mice, a mouse model of AD, to determine the effects of the diet in AD. Astrocytosis and microglia/monocyte activation were dramatically increased in response to diet and was further increased in APP/PS1 mice fed the western diet. This increase in glial responses was associated with increased plaque burden in the hippocampus. Interestingly, given recent studies highlighting the importance of TREM2 in microglia/monocytes in AD susceptibility and progression, B6 and APP/PS1 mice fed the western diet showed significant increases TREM2+ microglia/monocytes. Therefore, an increase in TREM2+ microglia/monocytes may underlie the increased risk from a western diet to age-related neurodegenerative diseases such as Alzheimer's disease. This study lays the foundation to fully investigate the impact of a western diet on glial responses in aging and Alzheimer's disease.

Estimating Effect Sizes and Expected Replication Probabilities from GWAS Summary Statistics

Genome-wide Association Studies (GWAS) result in millions of summary statistics (“z-scores”) for single nucleotide polymorphism (SNP) associations with phenotypes. These rich datasets afford deep insights into the nature and extent of genetic contributions to complex phenotypes such as psychiatric disorders, which are understood to have substantial genetic components that arise from very large numbers of SNPs. The complexity of the datasets, however, poses a significant challenge to maximizing their utility. This is reflected in a need for better understanding the landscape of z-scores, as such knowledge would enhance causal SNP and gene discovery, help elucidate mechanistic pathways, and inform future study design. Here we present a parsimonious methodology for modeling effect sizes and replication probabilities, relying only on summary statistics from GWAS substudies, and a scheme allowing for direct empirical validation. We show that modeling z-scores as a mixture of Gaussians is conceptually appropriate, in particular taking into account ubiquitous non-null effects that are likely in the datasets due to weak linkage disequilibrium with causal SNPs. The four-parameter model allows for estimating the degree of polygenicity of the phenotype and predicting the proportion of chip heritability explainable by genome-wide significant SNPs in future studies with larger sample sizes. We apply the model to recent GWAS of schizophrenia (N = 82,315) and putamen volume (N = 12,596), with approximately 9.3 million SNP z-scores in both cases. We show that, over a broad range of z-scores and sample sizes, the model accurately predicts expectation estimates of true effect sizes and replication probabilities in multistage GWAS designs. We assess the degree to which effect sizes are over-estimated when based on linear-regression association coefficients. We estimate the polygenicity of schizophrenia to be 0.037 and the putamen to be 0.001, while the respective sample sizes required to approach fully explaining the chip heritability are 10⁶ and 10⁵. The model can be extended to incorporate prior knowledge such as pleiotropy and SNP annotation. The current findings suggest that the model is applicable to a broad array of complex phenotypes and will enhance understanding of their genetic architectures.

ABCA1-Mediated Cholesterol Efflux Capacity to Cerebrospinal Fluid Is Reduced in Patients With Mild Cognitive Impairment and Alzheimer's Disease

Background

Animal and human studies indicate that ABCA1‐mediated cholesterol transport is important in Alzheimer's disease (AD). We hypothesized that the efficiency of cerebrospinal fluid (CSF) to facilitate ABCA1‐mediated cholesterol efflux would be reduced in participants with mild cognitive impairment (MCI) or AD compared with cognitively healthy participants.

Methods and Results

CSF was collected from a cross‐sectional study of cognitively healthy participants (n=47) and participants with MCI (n=35) or probable AD (n=26).The capacity of CSF to mediate cholesterol transport was assessed using a BHK cell line that can be induced to express the ABCA1 transporter. ABCA1‐mediated cholesterol efflux capacity was 30% less in participants with MCI or AD compared with cognitively healthy participants (P<0.001 for both). Cholesterol efflux capacity correlated with CSF cholesterol content (r=0.37, P<0.001). CSF phosphatidylcholine decreased in participants with MCI and AD compared with cognitively healthy participants (9% less in MCI and 27% less in AD compared with cognitively healthy participants, P=0.01) and correlated with CSF efflux capacity (r=0.3, P=0.001). CSF sphingomyelin also correlated with the efflux capacity (r=0.24, P=0.02). Concentrations of CSF apoA‐I and apoE did not significantly correlate with measures of efflux capacity.

Conclusions

In people with MCI and AD, the capacity of CSF to facilitate ABCA1‐mediated cholesterol efflux is impaired. This lesser cholesterol efflux in MCI supports a pathophysiological role for ABCA1‐mediated cholesterol transport in early neurodegeneration.

Regulation of neuronal gene expression by local axonal translation

RNA localization is a key mechanism in the regulation of protein expression. In neurons, this includes the axonal transport of select mRNAs based on the recognition of axonal localization motifs in these RNAs by RNA binding proteins. Bioinformatic analyses of axonal RNAs suggest that selective inclusion of such localization motifs in mature mRNAs is one mechanism controlling the composition of the axonal transcriptome. The subsequent translation of axonal transcripts in response to specific stimuli provides precise spatiotemporal control of the axonal proteome. This axonal translation supports local phenomena including axon pathfinding, mitochondrial function, and synapse-specific plasticity. Axonal protein synthesis also provides transport machinery and signals for retrograde trafficking to the cell body to effect somatic changes including altering the transcriptional program. Here we review the remarkable progress made in recent years to identify and characterize these phenomena.

Periodontal disease's contribution to Alzheimer's disease progression in Down syndrome

People with Down syndrome (DS) are at an increased risk for Alzheimer's disease (AD). After 60 years of age, >50% of DS subjects acquire dementia. Nevertheless, the age of onset is highly variable possibly because of both genetic and environmental factors. Genetics cannot be modified, but environmental risk factors present a potentially relevant intervention for DS persons at risk for AD. Among them, inflammation, important in AD of DS type, is potential target. Consistent with this hypothesis, chronic peripheral inflammation and infections may contribute to AD pathogenesis in DS. People with DS have an aggressive form of periodontitis characterized by rapid progression, significant bacterial and inflammatory burden, and an onset as early as 6 years of age. This review offers a hypothetical mechanistic link between periodontitis and AD in the DS population. Because periodontitis is a treatable condition, it may be a readily modifiable risk factor for AD.

Genetic and Transcriptomic Profiles of Inflammation in Neurodegenerative Diseases: Alzheimer, Parkinson, Creutzfeldt-Jakob and Tauopathies

Polymorphisms in certain inflammatory-related genes have been identified as putative differential risk factors of neurodegenerative diseases with abnormal protein aggregates, such as sporadic Alzheimer’s disease (AD) and sporadic Parkinson’s disease (sPD). Gene expression studies of cytokines and mediators of the immune response have been made in post-mortem human brain samples in AD, sPD, sporadic Creutzfeldt-Jakob disease (sCJD) subtypes MM1 and VV2, Pick’s disease (PiD), progressive supranuclear palsy (PSP) and frontotemporal lobar degeneration linked to mutation P301L in MAPT Frontotemporal lobar degeneration-tau (FTLD-tau). The studies have disclosed variable gene regulation which is: (1) disease-dependent in the frontal cortex area 8 in AD, sPD, sCJD MM1 and VV2, PiD, PSP and FTLD-tau; (2) region-dependent as seen when comparing the entorhinal cortex, orbitofrontal cortex, and frontal cortex area 8 (FC) in AD; the substantia nigra, putamen, FC, and angular gyrus in PD, as well as the FC and cerebellum in sCJD; (3) genotype-dependent as seen considering sCJD MM1 and VV2; and (4) stage-dependent as seen in AD at different stages of disease progression. These observations show that regulation of inflammation is much more complicated and diverse than currently understood, and that new therapeutic approaches must be designed in order to selectively act on specific targets in particular diseases and at different time points of disease progression.

Genetic variants near MLST8 and DHX57 affect the epigenetic age of the cerebellum

DNA methylation (DNAm) levels lend themselves for defining an epigenetic biomarker of aging known as the ‘epigenetic clock'. Our genome-wide association study (GWAS) of cerebellar epigenetic age acceleration identifies five significant (P<5.0 × 10⁻⁸) SNPs in two loci: 2p22.1 (inside gene DHX57) and 16p13.3 near gene MLST8 (a subunit of mTOR complex 1 and 2). We find that the SNP in 16p13.3 has a cis-acting effect on the expression levels of MLST8 (P=6.9 × 10⁻¹⁸) in most brain regions. In cerebellar samples, the SNP in 2p22.1 has a cis-effect on DHX57 (P=4.4 × 10⁻⁵). Gene sets found by our GWAS analysis of cerebellar age acceleration exhibit significant overlap with those of Alzheimer's disease (P=4.4 × 10⁻¹⁵), age-related macular degeneration (P=6.4 × 10⁻⁶), and Parkinson's disease (P=2.6 × 10⁻⁴). Overall, our results demonstrate the utility of a new paradigm for understanding aging and age-related diseases: it will be fruitful to use epigenetic tissue age as endophenotype in GWAS.

This genome-wide association study identifies five significant SNPs in two loci which are associated with the epigenetic age of post-mortem cerebellar tissue according to a DNA methylation based biomarker of human aging.

Discovery of gene-gene interactions across multiple independent data sets of late onset Alzheimer disease from the Alzheimer Disease Genetics Consortium

Late-onset Alzheimer disease (AD) has a complex genetic etiology, involving locus heterogeneity, polygenic inheritance, and gene-gene interactions; however, the investigation of interactions in recent genome-wide association studies has been limited. We used a biological knowledge-driven approach to evaluate gene-gene interactions for consistency across 13 data sets from the Alzheimer Disease Genetics Consortium. Fifteen single nucleotide polymorphism (SNP)-SNP pairs within 3 gene-gene combinations were identified: SIRT1 × ABCB1, PSAP × PEBP4, and GRIN2B × ADRA1A. In addition, we extend a previously identified interaction from an endophenotype analysis between RYR3 × CACNA1C. Finally, post hoc gene expression analyses of the implicated SNPs further implicate SIRT1 and ABCB1, and implicate CDH23 which was most recently identified as an AD risk locus in an epigenetic analysis of AD. The observed interactions in this article highlight ways in which genotypic variation related to disease may depend on the genetic context in which it occurs. Further, our results highlight the utility of evaluating genetic interactions to explain additional variance in AD risk and identify novel molecular mechanisms of AD pathogenesis.

Interaction between variants in CLU and MS4A4E modulates Alzheimer's disease risk

INTRODUCTION

Ebbert et al. reported gene-gene interactions between rs11136000-rs670139 (CLU-MS4A4E) and rs3865444-rs670139 (CD33-MS4A4E). We evaluate these interactions in the largest data set for an epistasis study.

METHODS

We tested interactions using 3837 cases and 4145 controls from Alzheimer's Disease Genetics Consortium using meta-analyses and permutation analyses. We repeated meta-analyses stratified by apolipoprotein E (APOE) ε4 status, estimated combined odds ratio (OR) and population attributable fraction (cPAF), and explored causal variants.

RESULTS

Results support the CLU-MS4A4E interaction and a dominant effect. An association between CLU-MS4A4E and APOE ε4 negative status exists. The estimated synergy factor, OR, and cPAF for rs11136000-rs670139 are 2.23, 2.45, and 8.0, respectively. We identified potential causal variants.

DISCUSSION

We replicated the CLU-MS4A4E interaction in a large case-control series and observed APOE ε4 and possible dominant effect. The CLU-MS4A4E OR is higher than any Alzheimer's disease locus except APOE ε4, APP, and TREM2. We estimated an 8% decrease in Alzheimer's disease incidence without CLU-MS4A4E risk alleles and identified potential causal variants.

Overlap between Parkinson disease and Alzheimer disease in ABCA7 functional variants

OBJECTIVE

Given their reported function in phagocytosis and clearance of protein aggregates in Alzheimer disease (AD), we hypothesized that variants in ATP-binding cassette transporter A7 (ABCA7) might be involved in Parkinson disease (PD).

METHODS

ABCA7 variants were identified using whole-exome sequencing (WES) on 396 unrelated patients with PD and 222 healthy controls. In addition, we used the publicly available WES data from the Parkinson's Progression Markers Initiative (444 patients and 153 healthy controls) as a second, independent data set.

RESULTS

We observed a higher frequency of loss-of-function (LOF) variants and rare putative highly functional variants (Combined Annotation Dependent Depletion [CADD] >20) in clinically diagnosed patients with PD than in healthy controls in both data sets. Overall, we identified LOF variants in 11 patients and 1 healthy control (odds ratio [OR] 4.94, Fisher exact p = 0.07). Four of these variants have been previously implicated in AD risk (p.E709AfsX86, p.W1214X, p.L1403RfsX7, and rs113809142). In addition, rare variants with CADD >20 were observed in 19 patients vs 3 healthy controls (OR 2.85, Fisher exact p = 0.06).

CONCLUSION

The presence of ABCA7 LOF variants in clinically defined PD suggests that they might be risk factors for neurodegeneration in general, especially those variants hallmarked by protein aggregation. More studies will be needed to evaluate the overall impact of this transporter in neurodegenerative disease.

Identification of Vulnerable Cell Types in Major Brain Disorders Using Single Cell Transcriptomes and Expression Weighted Cell Type Enrichment

The cell types that trigger the primary pathology in many brain diseases remain largely unknown. One route to understanding the primary pathological cell type for a particular disease is to identify the cells expressing susceptibility genes. Although this is straightforward for monogenic conditions where the causative mutation may alter expression of a cell type specific marker, methods are required for the common polygenic disorders. We developed the Expression Weighted Cell Type Enrichment (EWCE) method that uses single cell transcriptomes to generate the probability distribution associated with a gene list having an average level of expression within a cell type. Following validation, we applied EWCE to human genetic data from cases of epilepsy, Schizophrenia, Autism, Intellectual Disability, Alzheimer's disease, Multiple Sclerosis and anxiety disorders. Genetic susceptibility primarily affected microglia in Alzheimer's and Multiple Sclerosis; was shared between interneurons and pyramidal neurons in Autism and Schizophrenia; while intellectual disabilities and epilepsy were attributable to a range of cell-types, with the strongest enrichment in interneurons. We hypothesized that the primary cell type pathology could trigger secondary changes in other cell types and these could be detected by applying EWCE to transcriptome data from diseased tissue. In Autism, Schizophrenia and Alzheimer's disease we find evidence of pathological changes in all of the major brain cell types. These findings give novel insight into the cellular origins and progression in common brain disorders. The methods can be applied to any tissue and disorder and have applications in validating mouse models.

Identification of Vulnerable Cell Types in Major Brain Disorders Using Single Cell Transcriptomes and Expression Weighted Cell Type Enrichment

The cell types that trigger the primary pathology in many brain diseases remain largely unknown. One route to understanding the primary pathological cell type for a particular disease is to identify the cells expressing susceptibility genes. Although this is straightforward for monogenic conditions where the causative mutation may alter expression of a cell type specific marker, methods are required for the common polygenic disorders. We developed the Expression Weighted Cell Type Enrichment (EWCE) method that uses single cell transcriptomes to generate the probability distribution associated with a gene list having an average level of expression within a cell type. Following validation, we applied EWCE to human genetic data from cases of epilepsy, Schizophrenia, Autism, Intellectual Disability, Alzheimer's disease, Multiple Sclerosis and anxiety disorders. Genetic susceptibility primarily affected microglia in Alzheimer's and Multiple Sclerosis; was shared between interneurons and pyramidal neurons in Autism and Schizophrenia; while intellectual disabilities and epilepsy were attributable to a range of cell-types, with the strongest enrichment in interneurons. We hypothesized that the primary cell type pathology could trigger secondary changes in other cell types and these could be detected by applying EWCE to transcriptome data from diseased tissue. In Autism, Schizophrenia and Alzheimer's disease we find evidence of pathological changes in all of the major brain cell types. These findings give novel insight into the cellular origins and progression in common brain disorders. The methods can be applied to any tissue and disorder and have applications in validating mouse models.

Leveraging Genomic Annotations and Pleiotropic Enrichment for Improved Replication Rates in Schizophrenia GWAS

Most of the genetic architecture of schizophrenia (SCZ) has not yet been identified. Here, we apply a novel statistical algorithm called Covariate-Modulated Mixture Modeling (CM3), which incorporates auxiliary information (heterozygosity, total linkage disequilibrium, genomic annotations, pleiotropy) for each single nucleotide polymorphism (SNP) to enable more accurate estimation of replication probabilities, conditional on the observed test statistic (“z-score”) of the SNP. We use a multiple logistic regression on z-scores to combine information from auxiliary information to derive a “relative enrichment score” for each SNP. For each stratum of these relative enrichment scores, we obtain nonparametric estimates of posterior expected test statistics and replication probabilities as a function of discovery z-scores, using a resampling-based approach that repeatedly and randomly partitions meta-analysis sub-studies into training and replication samples. We fit a scale mixture of two Gaussians model to each stratum, obtaining parameter estimates that minimize the sum of squared differences of the scale-mixture model with the stratified nonparametric estimates. We apply this approach to the recent genome-wide association study (GWAS) of SCZ (n = 82,315), obtaining a good fit between the model-based and observed effect sizes and replication probabilities. We observed that SNPs with low enrichment scores replicate with a lower probability than SNPs with high enrichment scores even when both they are genome-wide significant (p < 5x10^-8). There were 693 and 219 independent loci with model-based replication rates ≥80% and ≥90%, respectively. Compared to analyses not incorporating relative enrichment scores, CM3 increased out-of-sample yield for SNPs that replicate at a given rate. This demonstrates that replication probabilities can be more accurately estimated using prior enrichment information with CM3.

Genome-wide association studies (GWAS) have thus far identified only a small fraction of the heritability of common complex disorders, such as schizophrenia. Here, we demonstrate that by using auxiliary information we can improve estimates of replication probabilities from GWAS summary statistics. The proposed Covariate-Modulated Mixture Model (CM3) incorporates auxiliary information to construct an “enrichment score” for each single nucleotide polymorphism (SNP). We show that a scale mixture of two Gaussians provides a good fit to the observed effect size distribution stratified by the predicted enrichment score when applied the method to a recent genome-wide association study (GWAS) of SCZ (n = 82,315). Compared to estimates performed not using auxiliary information, the CM3 more accurately models the observed replication rates by stratifying on covariate-modulated enrichment scores. We observed that SNPs with low enrichment scores replicate with a lower probability compared to SNPs with high enrichment scores, even when both are genome-wide significant (p < 5x10^-8). At model-based replication rates ≥80% and ≥90% there were 693 and 219 independent loci, respectively. Increased out-of-sample yield for SNPs ranked according to CM3 demonstrate the utility of incorporating auxiliary information via CM3.

An Overview of Genome-Wide Association Studies in Alzheimer's Disease

Genome-wide association studies (GWASs) have revealed a plethora of putative susceptibility genes for Alzheimer's disease (AD). With the sole exception of the APOE gene, these AD susceptibility genes have not been unequivocally validated in independent studies. No single novel functional risk genetic variant has been identified. In this review, we evaluate recent GWASs of AD, and discuss their significance, limitations, and challenges in the investigation of the genetic spectrum of AD.

Modeling of Platinum-Aryl Interaction with Amyloid-β Peptide

Ligand field molecular mechanics (LFMM), density functional theory (DFT), and semiempirical PM7 methods are used to study the binding of two Pt(II)-L systems to an N-terminal fragment of the amyloid-β peptide, where L = 2,2-bipyridyl or 1,10-phenanthroline. Molecular dynamics simulations are used to explore the conformational freedom of the peptide using LFMM combined with AMBER molecular mechanics parameters. We establish a modeling protocol, allowing for identification and analysis of favorable platinum-binding modes and peptide conformations. Preferred binding modes are identified for each ligand investigated; metal coordination occurs via Nε in His residues for both ligands--His6ε-His13ε and His6ε-His14ε for the bipyridyl and phenanthroline ligands, respectively. The observed change in binding mode for the different ligands suggests that the binding mode of these platinum-based structures can be controlled by the choice of ligand. In the bipy systems, Boltzmann population at 310 K is dominated by a single conformer, while in the phenanthroline case, three conformations make significant contributions to the ensemble. The relative stability of these conformations is due to the inherent stability of binding platinum via Nε in addition to subtle H-bonding effects.

Associations Between Genetic Variants in 19p13 and 19q13 Regions and Susceptibility to Alzheimer Disease: A Meta-Analysis

BACKGROUND

Alzheimer disease (AD) has become an epidemic within the growing elderly population and effective therapies of AD have not been discovered. Genetic factors accounted for over 70% of the incidence of AD and the disease-related polymorphisms are located on chromosome 19, which is one of several prominent chromosomes related to the development of AD. Many inconsistent associations between polymorphisms in ABCA7, CD33, and TOMM40 genes and the susceptibility to AD have been suggested by several independent studies.

MATERIAL/METHODS

A comprehensive literature search for studies involving the association between gene polymorphisms and AD was performed, and we finally selected 3 genes (4 polymorphisms) for the meta-analysis: ABCA7 (rs3764650), CD33 (rs3865444), and TOMM40 (rs157580, rs2075650).

RESULTS

A total of 25 articles investigating 3 genes (4 polymorphisms) were included in the meta-analysis. The pooled results of 4 polymorphisms were all significantly associated with the susceptibility to AD. The pooled effect of ABCA7 rs3764605 allele G was significantly associated with an increased the risk of AD (OR=1.20, 95% CI: 1.14-1.26, P value <0.001). Similarly, our evidence suggested that allele A of TOMM40 rs2075650 polymorphism was a risk factor for AD (OR=2.87, 95% CI: 2.46-3.34, P value <0.001). Alleles A of CD33 rs3865444 and A of TOMM40 rs157580 were both protective factors for AD onset (OR=0.94, 95% CI: 0.90-0.98, P value=0.003; OR=0.62, 95% CI: 0.57-0.66, P value <0.001). CONCLUSIONS" Results from the meta-analysis revealed that the pooled ABCA7 rs376465, CD33 rs3865444, TOMM40 rs157580, and rs2075650 variants were significantly associated with the susceptibility to AD. However, the association differed significantly between Asian and Caucasian groups for SNPs of CD33 rs3865444, TOMM40 rs157580, and rs2075650.

A Missense Variant in TREML2 Reduces Risk of Alzheimer's Disease in a Han Chinese Population

Recently, Benitez and colleagues re-analyzed whole-exome sequencing data and revealed that a coding missense variant (rs3747742-C) in triggering receptor expressed on myeloid cells-like 2 (TREML2) gene reduced late-onset Alzheimer's disease (LOAD) risk in Caucasians. To date, no study was carried out to test this association in other ethnic groups and populations, including Han Chinese. Therefore, the aim of the current study was to validate the relation between rs3747742 and LOAD susceptibility in a large Han Chinese population including 992 LOAD patients and 1358 healthy controls. In the total sample, the minor (C) allele of rs3747742 was associated with a reduced LOAD risk under the recessive genetic model after Bonferroni correction (odds ratio (OR) = 0.713; 95 % confidence interval (CI): 0.546-0.932; P = 0.013, Bonferroni-corrected P = 0.039). Interestingly, after stratifying data according to apolipoprotein E (APOE) ε4 status, we revealed that this protection only exists in APOE ε4 carriers (recessive genetic model, OR = 0.448; 95 % CI: 0.262-0.765; P = 0.003, Bonferroni-corrected P = 0.009) in our cohort. Taken together, our findings support rs3747742-C as a protective factor for LOAD, especially in APOE ε4 carriers.

Inhibition of Aβ42 oligomerization in yeast by a PICALM ortholog and certain FDA approved drugs

The formation of small Aβ₄₂ oligomers has been implicated as a toxic species in Alzheimer disease (AD). In strong support of this hypothesis we found that overexpression of Yap1802, the yeast ortholog of the human AD risk factor, phosphatidylinositol binding clathrin assembly protein (PICALM), reduced oligomerization of Aβ₄₂ fused to a reporter in yeast. Thus we used the Aβ₄₂-reporter system to identify drugs that could be developed into therapies that prevent or arrest AD. From a screen of 1,200 FDA approved drugs and drug-like small compounds we identified 7 drugs that reduce Aβ₄₂ oligomerization in yeast: 3 antipsychotics (bromperidol, haloperidol and azaperone), 2 anesthetics (pramoxine HCl and dyclonine HCl), tamoxifen citrate, and minocycline HCl. Also, all 7 drugs caused Aβ₄₂ to be less toxic to PC12 cells and to relieve toxicity of another yeast AD model in which Aβ₄₂ aggregates targeted to the secretory pathway are toxic. Our results identify drugs that inhibit Aβ₄₂ oligomers from forming in yeast. It remains to be determined if these drugs inhibit Aβ₄₂ oligomerization in mammals and could be developed as a therapeutic treatment for AD.

Abca7 deletion does not affect adult neurogenesis in the mouse

ATP-binding cassette transporter A7 (ABCA7) is expressed in the brain and linked with Alzheimer's disease. Since other ABC transporters regulate adult neurogenesis, we assessed neurogenesis in wild-type (WT) and Abca7 deficient mice. Abca7 deletion did not affect adult neurogenesis in the mouse.

ATP-binding cassette transporter A7 (ABCA7) is highly expressed in the brain. Recent genome-wide association studies (GWAS) have identified ABCA7 single nucleotide polymorphisms (SNPs) that increase Alzheimer's disease (AD) risk, however, the mechanisms by which ABCA7 may control AD risk remain to be fully elucidated. Based on previous research suggesting that certain ABC transporters may play a role in the regulation of neurogenesis, we conducted a study of cell proliferation and neurogenic potential using cellular bromodeoxyuridine (BrdU) incorporation and doublecortin (DCX) immunostaining in adult Abca7 deficient mice and wild-type-like (WT) littermates. In the present study counting of BrdU-positive and DCX-positive cells in an established adult neurogenesis site in the dentate gyrus (DG) indicated there were no significant differences when WT and Abca7 deficient mice were compared. We also measured the area occupied by immunohistochemical staining for BrdU and DCX in the DG and the subventricular zone (SVZ) of the same mice and this confirmed that ABCA7 does not play a significant role in the regulation of cell proliferation or neurogenesis in the adult mouse.

Genome-wide DNA methylation profiling in the superior temporal gyrus reveals epigenetic signatures associated with Alzheimer's disease

BACKGROUND

Alzheimer's disease affects ~13% of people in the United States 65 years and older, making it the most common neurodegenerative disorder. Recent work has identified roles for environmental, genetic, and epigenetic factors in Alzheimer's disease risk.

METHODS

We performed a genome-wide screen of DNA methylation using the Illumina Infinium HumanMethylation450 platform on bulk tissue samples from the superior temporal gyrus of patients with Alzheimer's disease and non-demented controls. We paired a sliding window approach with multivariate linear regression to characterize Alzheimer's disease-associated differentially methylated regions (DMRs).

RESULTS

We identified 479 DMRs exhibiting a strong bias for hypermethylated changes, a subset of which were independently associated with aging. DMR intervals overlapped 475 RefSeq genes enriched for gene ontology categories with relevant roles in neuron function and development, as well as cellular metabolism, and included genes reported in Alzheimer's disease genome-wide and epigenome-wide association studies. DMRs were enriched for brain-specific histone signatures and for binding motifs of transcription factors with roles in the brain and Alzheimer's disease pathology. Notably, hypermethylated DMRs preferentially overlapped poised promoter regions, marked by H3K27me3 and H3K4me3, previously shown to co-localize with aging-associated hypermethylation. Finally, the integration of DMR-associated single nucleotide polymorphisms with Alzheimer's disease genome-wide association study risk loci and brain expression quantitative trait loci highlights multiple potential DMRs of interest for further functional analysis.

CONCLUSION

We have characterized changes in DNA methylation in the superior temporal gyrus of patients with Alzheimer's disease, highlighting novel loci that facilitate better characterization of pathways and mechanisms underlying Alzheimer's disease pathogenesis, and improve our understanding of epigenetic signatures that may contribute to the development of disease.

Network-based analysis of genetic variants associated with hippocampal volume in Alzheimer's disease: a study of ADNI cohorts

Background

Alzheimer’s disease (AD) is a neurodegenerative disease that causes dementia. While molecular basis of AD is not fully understood, genetic factors are expected to participate in the development and progression of the disease. Our goal was to uncover novel genetic underpinnings of Alzheimer’s disease with a bioinformatics approach that accounts for tissue specificity.

Findings

We performed genome-wide association studies (GWAS) for hippocampal volume in two Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohorts. We used these GWAS in a subsequent tissue-specific network-wide association study (NetWAS), which applied nominally significant associations in the initial GWAS to identify disease relevant patterns in a functional network for the hippocampus. We compared prioritized gene lists from NetWAS and GWAS with literature curated AD-associated genes from the Online Mendelian Inheritance in Man (OMIM) database. In the ADNI-1 GWAS, where we also observed an enrichment of low p-values, NetWAS prioritized disease-gene associations in accordance with OMIM annotations. This was not observed in the ADNI-2 dataset. We provide source code to replicate these analyses as well as complete results under permissive licenses.

Conclusions

We performed the first analysis of hippocampal volume using NetWAS, which uses machine learning algorithms applied to tissue-specific functional interaction network to prioritize GWAS results. Our findings support the idea that tissue-specific networks may provide helpful context for understanding the etiology of common human diseases and reveal challenges that network-based approaches encounter in some datasets. Our source code and intermediate results files can facilitate the development of methods to address these challenges.

Electronic supplementary material

The online version of this article (doi:10.1186/s13040-016-0082-8) contains supplementary material, which is available to authorized users.

Dissecting risk haplotypes in sporadic Alzheimer's disease

Understanding how genetic risk variants contribute to complex diseases is crucial for predicting disease susceptibility and developing patient-tailored therapies. In this issue of Cell Stem Cell, Young et al. (2015) dissect the function of common non-coding risk haplotypes in the SORL1 locus in the pathogenesis of sporadic Alzheimer's disease using patient-derived induced pluripotent stem cells.

Segregation of a rare TTC3 variant in an extended family with late-onset Alzheimer disease

OBJECTIVE

The genetic risk architecture of Alzheimer disease (AD) is complex with single pathogenic mutations leading to early-onset AD, while both rare and common genetic susceptibility variants contribute to the more widespread late-onset AD (LOAD); we sought to discover novel genes contributing to LOAD risk.

METHODS

Whole-exome sequencing and genome-wide genotyping were performed on 11 affected individuals in an extended family with an apparent autosomal dominant pattern of LOAD. Variants of interest were then evaluated in a large cohort of LOAD cases and aged controls.

RESULTS

We detected a single rare, nonsynonymous variant shared in all 11 LOAD individuals, a missense change in the tetratricopeptide repeat domain 3 (TTC3) gene. The missense variant, rs377155188 (p.S1038C), is predicted to be damaging. Affecteds-only multipoint linkage analysis demonstrated that this region of TTC3 has a LOD score of 2.66 in this family.

CONCLUSION

The TTC3 p.S1038C substitution may represent a segregating, rare LOAD risk variant. Previous studies have shown that TTC3 expression is consistently reduced in LOAD patients and negatively correlated with AD neuropathology and that TTC3 is a regulator of Akt signaling, a key pathway disrupted in LOAD. This study demonstrates how utilizing whole-exome sequencing in a large, multigenerational family with a high incidence of LOAD could reveal a novel candidate gene.

Genetic Determinants of Survival in Patientswith Alzheimer’s Disease

There is a strong genetic basis for late-onset of Alzheimer’s disease (LOAD), and thus far >20 genes/loci have been identified that affect the risk of LOAD. In addition to disease risk, genetic variation at these loci may also affect components of the natural history of AD, such as survival in AD. In this study, we first examined the role of known LOAD genes with survival time in 983 AD patients. We then performed genome-wide single-nucleotide polymorphism (SNP) and gene-based association analyses to identify novel loci that may influence survival of AD. Survival analysis was conducted using Cox proportional hazards regression under an additive genetics model. We found multiple nominally significant associations (p < 0.01) either within or adjacent to known LOAD genes. Genome-wide SNP analysis identified multiple suggestive novel loci and two of them were also significant in gene-based analysis (CCDC85C and NARS2) that survived after controlling for false-discovery rate at 0.05. In summary, we have identified two novel genes for survival in AD that need to be replicated in independent samples. Our findings highlight the importance of focusing on AD-related phenotypes that may help to identify additional genes relevant toAD.

Sports genetics moving forward: lessons learned from medical research

Sports genetics can take advantage of lessons learned from human disease genetics. By righting past mistakes and increasing scientific rigor, we can magnify the breadth and depth of knowledge in the field. We present an outline of challenges facing sports genetics in the light of experiences from medical research. Sports performance is complex, resulting from a combination of a wide variety of different traits and attributes. Improving sports genetics will foremost require analyses based on detailed phenotyping. To find widely valid, reproducible common variants associated with athletic phenotypes, study sample sizes must be dramatically increased. One paradox is that in order to confirm relevance, replications in specific populations must be undertaken. Family studies of athletes may facilitate the discovery of rare variants with large effects on athletic phenotypes. The complexity of the human genome, combined with the complexity of athletic phenotypes, will require additional metadata and biological validation to identify a comprehensive set of genes involved. Analysis of personal genetic and multiomic profiles contribute to our conceptualization of precision medicine; the same will be the case in precision sports science. In the refinement of sports genetics it is essential to evaluate similarities and differences between sexes and among ethnicities. Sports genetics to date have been hampered by small sample sizes and biased methodology, which can lead to erroneous associations and overestimation of effect sizes. Consequently, currently available genetic tests based on these inherently limited data cannot predict athletic performance with any accuracy.

Pharmacological targeting of CSF1R inhibits microglial proliferation and prevents the progression of Alzheimer's-like pathology

The proliferation and activation of microglial cells is a hallmark of several neurodegenerative conditions. This mechanism is regulated by the activation of the colony-stimulating factor 1 receptor (CSF1R), thus providing a target that may prevent the progression of conditions such as Alzheimer’s disease. However, the study of microglial proliferation in Alzheimer’s disease and validation of the efficacy of CSF1R-inhibiting strategies have not yet been reported. In this study we found increased proliferation of microglial cells in human Alzheimer’s disease, in line with an increased upregulation of the CSF1R-dependent pro-mitogenic cascade, correlating with disease severity. Using a transgenic model of Alzheimer’s-like pathology (APPswe, PSEN1dE9; APP/PS1 mice) we define a CSF1R-dependent progressive increase in microglial proliferation, in the proximity of amyloid-β plaques. Prolonged inhibition of CSF1R in APP/PS1 mice by an orally available tyrosine kinase inhibitor (GW2580) resulted in the blockade of microglial proliferation and the shifting of the microglial inflammatory profile to an anti-inflammatory phenotype. Pharmacological targeting of CSF1R in APP/PS1 mice resulted in an improved performance in memory and behavioural tasks and a prevention of synaptic degeneration, although these changes were not correlated with a change in the number of amyloid-β plaques. Our results provide the first proof of the efficacy of CSF1R inhibition in models of Alzheimer’s disease, and validate the application of a therapeutic strategy aimed at modifying CSF1R activation as a promising approach to tackle microglial activation and the progression of Alzheimer’s disease.

The A-B-C for SORting APP

This Editorial highlights a study by Hermey and colleagues in the current issue of Journal of Neurochemistry. In their study, the authors provide novel insights into single-nucleotide polymorphisms associated with Alzheimer's disease and linked to the SorCS1 gene, toward a better understanding of the interaction of sorting receptor proteins which physically interact with the amyloid-beta protein precursor (APP). SorCS1, sortilin-related VPS10 domain-containing receptor 1; SorLA, sortilin-related Receptor with A-type Repeats. Read the full article 'SorCS1 variants and amyloid precursor protein (APP) are co-transported in neurons but only SorCS1c modulates anterograde APP transport' on page 60.

GWAS-Linked Loci and Neuroimaging Measures in Alzheimer's Disease

Recently, 19 susceptibility loci for Alzheimer's disease (AD) had been identified through AD genome-wide association studies (GWAS) meta-analysis. However, how they influence the pathogenesis of AD still remains largely unknown. We studied those loci with six MRI measures, abnormal glucose metabolism, and β-amyloid (Aβ) deposition on neuroimaging in a large cohort from Alzheimer's Disease Neuroimaging Initiative (ADNI) database in order to provide clues of the mechanisms through which these genetic variants might be acting. As a result, single nucleotide polymorphisms (SNPs) at rs983392 within MS4A6A and rs11218343 within SOLR1 were both associated with the percentage of increase in the volume of left inferior temporal regions in the follow-up study. Meanwhile, rs11218343 at SORL1 and rs6733839 at BIN1 was associated with rate of volume change of left parahippocampal and right inferior parietal, respectively. Moreover, rs6656401 at CR1 and rs983392 at MS4A6A were both associated with smaller volume of right middle temporal at baseline. However, in addition to the APOE locus, we did not detect any influence on glucose metabolism and Aβ deposition. APOE ε4 allele was associated with almost all measures. Altogether, five loci (rs6656401 at CR1, rs983392within MS4A6A, rs11218343 at SORL1, rs6733839 at BIN1, and APOE ε4) have been detected to be associated with one or a few established AD-related neuroimaging measures.

Diabetic Phenotypes and Late-Life Dementia Risk: A Mechanism-specific Mendelian Randomization Study

BACKGROUND

Mendelian Randomization (MR) studies have reported that type 2 diabetes (T2D) was not associated with Alzheimer disease (AD). We adopted a modified, mechanism-specific MR design to explore this surprising result.

METHODS

Using inverse-variance weighted MR analysis, we evaluated the association between T2D and AD using data from 39 single nucleotide polymorphisms (SNPs) significantly associated with T2D in DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) and the corresponding associations of each SNP with AD risk obtained from the International Genomics of Alzheimer's Project (IGAP, n=17,008 AD cases and n=37,154 controls). We evaluated mechanism-specific genetic subscores, including β-cell function, insulin sensitivity, and adiposity, and repeated analyses in 8501 Health and Retirement Study participants for replication and model validation.

RESULTS

In IGAP, the overall T2D polygenic score did not predict AD [odds ratio (OR) for the T2D polygenic score=1.01; 95% confidence interval (CI), 0.96, 1.06] but the insulin sensitivity polygenic score predicted higher AD risk (OR=1.17; 95% CI, 1.02, 1.34). In the Health and Retirement Study, polygenic scores were associated with T2D risk; the associations between insulin sensitivity genetic polygenic score and cognitive phenotypes were not statistically significant.

CONCLUSIONS

Evidence from polygenic scores suggests that insulin sensitivity specifically may affect AD risk, more than T2D overall.

Next Generation Sequencing in Alzheimer's Disease

For the first time in the history of human genetics research, it is now both technically feasible and economically affordable to screen individual genomes for novel disease-causing mutations at base-pair resolution using "next-generation sequencing" (NGS). One popular aim in many of today's NGS studies is genome resequencing (in part or whole) to identify DNA variants potentially accounting for the "missing heritability" problem observed in many genetically complex traits. Thus far, only relatively few projects have applied these powerful new technologies to search for novel Alzheimer's disease (AD) related sequence variants. In this review, I summarize the findings from the first NGS-based resequencing studies in AD and discuss their potential implications and limitations. Notable recent discoveries using NGS include the identification of rare susceptibility modifying alleles in APP, TREM2, and PLD3. Several other large-scale NGS projects are currently underway so that additional discoveries can be expected over the coming years.

Methylation QTLs in the developing brain and their enrichment in schizophrenia risk loci

We characterized DNA methylation quantitative trait loci (mQTLs) in a large collection (n = 166) of human fetal brain samples spanning 56-166 d post-conception, identifying >16,000 fetal brain mQTLs. Fetal brain mQTLs were primarily cis-acting, enriched in regulatory chromatin domains and transcription factor binding sites, and showed substantial overlap with genetic variants that were also associated with gene expression in the brain. Using tissue from three distinct regions of the adult brain (prefrontal cortex, striatum and cerebellum), we found that most fetal brain mQTLs were developmentally stable, although a subset was characterized by fetal-specific effects. Fetal brain mQTLs were enriched amongst risk loci identified in a recent large-scale genome-wide association study (GWAS) of schizophrenia, a severe psychiatric disorder with a hypothesized neurodevelopmental component. Finally, we found that mQTLs can be used to refine GWAS loci through the identification of discrete sites of variable fetal brain methylation associated with schizophrenia risk variants.

Genome-wide estimate of the heritability of Multiple System Atrophy

INTRODUCTION

Multiple System Atrophy (MSA) is a neurodegenerative disease which presents heterogeneously with symptoms and signs of parkinsonism, ataxia and autonomic dysfunction. Although MSA typically occurs sporadically, rare pathology-proven MSA families following either autosomal recessive or autosomal dominant patterns have been described, indicating a heritable contribution to the pathogenesis.

METHODS

We used Genome-Wide Complex Trait Analysis (GCTA) to estimate the heritable component of MSA due to common coding variability in imputed genotype data of 907 MSA cases and 3866 population-matched controls. GCTA only assesses the effect of putative causal variants in linkage disequilibrium (LD) with all common SNPs on the genotyping platform.

RESULTS

We estimate the heritability among common variants of MSA in pooled cases at 2.09-6.65%, with a wider range of values in geographic and diagnostic subgroups. Meta-analysis of our geographic cohorts reveals high between-group heterogeneity. Contributions of single chromosomes are generally negligible. We suggest that all calculated MSA heritability among common variants could be explained by the presence of misdiagnosed cases in the clinical subgroup based on a Bayesian estimate using literature-derived rates of misdiagnosis.

DISCUSSION

MSA is a challenging disease to study due to high rates of misdiagnosis and low prevalence. Given our low estimates of heritability, common genetic variation appears to play a less prominent role in risk for MSA than in other complex neurodegenerative diseases such as Parkinson's disease, Alzheimer's disease, and Amyotrophic Lateral Sclerosis. The success of future gene discovery efforts rests on large pathologically-confirmed case series and an interrogation of both common and rare genetic variants.