Matthew J. Huentelman

GAB2 Alleles Modify Alzheimer's Risk in APOE ε4 Carriers

The apolipoprotein E (APOE) epsilon4 allele is the best established genetic risk factor for late-onset Alzheimers disease (LOAD). We conducted genome-wide surveys of 502,627 single-nucleotide polymorphisms (SNPs) to characterize and confirm other LOAD susceptibility genes. In epsilon4 carriers from neuropathologically verified discovery, neuropathologically verified replication, and clinically characterized replication cohorts of 1411 cases and controls, LOAD was associated with six SNPs from the GRB-associated binding protein 2 (GAB2) gene and a common haplotype encompassing the entire GAB2 gene. SNP rs2373115 (p = 9 x 10(-11)) was associated with an odds ratio of 4.06 (confidence interval 2.81-14.69), which interacts with APOE epsilon4 to further modify risk. GAB2 was overexpressed in pathologically vulnerable neurons; the Gab2 protein was detected in neurons, tangle-bearing neurons, and dystrophic neuritis; and interference with GAB2 gene expression increased tau phosphorylation. Our findings suggest that GAB2 modifies LOAD risk in APOE epsilon4 carriers and influences Alzheimers neuropathology.

A survey of genetic human cortical gene expression

It is widely assumed that genetic differences in gene expression underpin much of the difference among individuals and many of the quantitative traits of interest to geneticists. Despite this, there has been little work on genetic variability in human gene expression and almost none in the human brain, because tools for assessing this genetic variability have not been available. Now, with whole-genome SNP genotyping arrays and whole-transcriptome expression arrays, such experiments have become feasible. We have carried out whole-genome genotyping and expression analysis on a series of 193 neuropathologically normal human brain samples using the Affymetrix GeneChip Human Mapping 500K Array Set and Illumina HumanRefseq-8 Expression BeadChip platforms. Here we present data showing that 58% of the transcriptome is cortically expressed in at least 5% of our samples and that of these cortically expressed transcripts, 21% have expression profiles that correlate with their genotype. These genetic-expression effects should be useful in determining the underlying biology of associations with common diseases of the human brain and in guiding the analysis of the genomic regions involved in the control of normal gene expression.

Identification of genetic variants using bar-coded multiplexed sequencing.

We developed a generalized framework for multiplexed resequencing of targeted human genome regions on the Illumina Genome Analyzer using degenerate indexed DNA bar codes ligated to fragmented DNA before sequencing. Using this method, we simultaneously sequenced the DNA of multiple HapMap individuals at several Encyclopedia of DNA Elements (ENCODE) regions. We then evaluated the use of Bayes factors for discovering and genotyping polymorphisms. For polymorphisms that were either previously identified within the Single Nucleotide Polymorphism database (dbSNP) or visually evident upon re-inspection of archived ENCODE traces, we observed a false positive rate of 11.3% using strict thresholds for predicting variants and 69.6% for lax thresholds. Conversely, false negative rates were 10.8–90.8%, with false negatives at stricter cut-offs occurring at lower coverage (<10 aligned reads). These results suggest that >90% of genetic variants are discoverable using multiplexed sequencing provided sufficient coverage at the polymorphic base.

A TOMM40 variable-length polymorphism predicts the age of late-onset Alzheimer's disease.

The ɛ4 allele of the apolipoprotein E (APOE) gene is currently the strongest and most highly replicated genetic factor for risk and age of onset of late-onset Alzheimers disease (LOAD). Using phylogenetic analysis, we have identified a polymorphic poly-T variant, rs10524523, in the translocase of outer mitochondrial membrane 40 homolog (TOMM40) gene that provides greatly increased precision in the estimation of age of LOAD onset for APOE ɛ3 carriers. In two independent clinical cohorts, longer lengths of rs10524523 are associated with a higher risk for LOAD. For APOE ɛ3/4 patients who developed LOAD after 60 years of age, individuals with long poly-T repeats linked to APOE ɛ3 develop LOAD on an average of 7 years earlier than individuals with shorter poly-T repeats linked to APOE ɛ3 (70.5±1.2 years versus 77.6±2.1 years, P=0.02, n=34). Independent mutation events at rs10524523 that occurred during Caucasian evolution have given rise to multiple categories of poly-T length variants at this locus. On replication, these results will have clinical utility for predictive risk estimates for LOAD and for enabling clinical disease prevention studies. In addition, these results show the effective use of a phylogenetic approach for analysis of haplotypes of polymorphisms, including structural polymorphisms, which contribute to complex diseases.

Brain imaging and fluid biomarker analysis in young adults at genetic risk for autosomal dominant Alzheimer's disease in the presenilin 1 E280A kindred: a case-control study

BACKGROUND We have previously characterised functional brain abnormalities in young adults at genetic risk for late-onset Alzheimers disease. To gain further knowledge on the preclinical phase of Alzheimers disease, we sought to characterise structural and functional MRI, CSF, and plasma biomarkers in a cohort of young adults carrying a high-penetrance autosomal dominant mutation that causes early-onset Alzheimers disease. METHODS Between January and August, 2010, 18-26-year-old presenilin 1 (PSEN1) E280A mutation carriers and non-carriers from the Colombian Alzheimers Prevention Initiative Registry in Medellín Antioquia, Colombia, had structural MRI, functional MRI during associative memory encoding and novel viewing and control tasks, and cognitive assessments. Consenting participants also had lumbar punctures and venepunctures. Outcome measures were task-dependent hippocampal or parahippocampal activations and precuneus or posterior cingulate deactivations, regional grey matter reductions, CSF Aβ(1-42), total tau and phospho-tau(181) concentrations, and plasma Aβ(1-42) concentrations and Aβ(1-42):Aβ(1-40) ratios. Structural and functional MRI data were compared using automated brain mapping algorithms and search regions related to Alzheimers disease. Cognitive and fluid biomarkers were compared using Mann-Whitney tests. FINDINGS 44 participants were included: 20 PSEN1 E280A mutation carriers and 24 non-carriers. The carrier and non-carrier groups did not differ significantly in their dementia ratings, neuropsychological test scores, or proportion of apolipoprotein E (APOE) ɛ4 carriers. Compared with non-carriers, carriers had greater right hippocampal and parahippocampal activation (p=0·001 and p<0·014, respectively, after correction for multiple comparisons), less precuneus and posterior cingulate deactivation (all p<0·010 after correction), and less grey matter in several parietal regions (all p<0·002 uncorrected and corrected p=0·009 in the right parietal search region). In the 20 participants (ten PSEN1 E280A mutation carriers and ten non-carriers) who had lumbar punctures and venepunctures, mutation carriers had higher CSF Aβ(1-42) concentrations (p=0·008) and plasma Aβ(1-42) concentrations (p=0·01) than non-carriers. INTERPRETATION Young adults at genetic risk for autosomal dominant Alzheimers disease have functional and structural MRI findings and CSF and plasma biomarker findings consistent with Aβ(1-42) overproduction. Although the extent to which the underlying brain changes are either neurodegenerative or developmental remain to be determined, this study shows the earliest known biomarker changes in cognitively normal people at genetic risk for autosomal dominant Alzheimers disease. FUNDING Banner Alzheimers Foundation, Nomis Foundation, Anonymous Foundation, Forget Me Not Initiative, Boston University Department of Psychology, Colciencias, National Institute on Aging, National Institute of Neurological Disorders and Stroke, and the State of Arizona.

Whole genome association study of brain-wide imaging phenotypes for identifying quantitative trait loci in MCI and AD: A study of the ADNI cohort

A genome-wide, whole brain approach to investigate genetic effects on neuroimaging phenotypes for identifying quantitative trait loci is described. The Alzheimers Disease Neuroimaging Initiative 1.5 T MRI and genetic dataset was investigated using voxel-based morphometry (VBM) and FreeSurfer parcellation followed by genome-wide association studies (GWAS). One hundred forty-two measures of grey matter (GM) density, volume, and cortical thickness were extracted from baseline scans. GWAS, using PLINK, were performed on each phenotype using quality-controlled genotype and scan data including 530,992 of 620,903 single nucleotide polymorphisms (SNPs) and 733 of 818 participants (175 AD, 354 amnestic mild cognitive impairment, MCI, and 204 healthy controls, HC). Hierarchical clustering and heat maps were used to analyze the GWAS results and associations are reported at two significance thresholds (p<10(-7) and p<10(-6)). As expected, SNPs in the APOE and TOMM40 genes were confirmed as markers strongly associated with multiple brain regions. Other top SNPs were proximal to the EPHA4, TP63 and NXPH1 genes. Detailed image analyses of rs6463843 (flanking NXPH1) revealed reduced global and regional GM density across diagnostic groups in TT relative to GG homozygotes. Interaction analysis indicated that AD patients homozygous for the T allele showed differential vulnerability to right hippocampal GM density loss. NXPH1 codes for a protein implicated in promotion of adhesion between dendrites and axons, a key factor in synaptic integrity, the loss of which is a hallmark of AD. A genome-wide, whole brain search strategy has the potential to reveal novel candidate genes and loci warranting further investigation and replication.

Genetic Control of Human Brain Transcript Expression in Alzheimer Disease

We recently surveyed the relationship between the human brain transcriptome and genome in a series of neuropathologically normal postmortem samples. We have now analyzed additional samples with a confirmed pathologic diagnosis of late-onset Alzheimer disease (LOAD; final n = 188 controls, 176 cases). Nine percent of the cortical transcripts that we analyzed had expression profiles correlated with their genotypes in the combined cohort, and approximately 5% of transcripts had SNP-transcript relationships that could distinguish LOAD samples. Two of these transcripts have been previously implicated in LOAD candidate-gene SNP-expression screens. This study shows how the relationship between common inherited genetic variants and brain transcript expression can be used in the study of human brain disorders. We suggest that studying the transcriptome as a quantitative endo-phenotype has greater power for discovering risk SNPs influencing expression than the use of discrete diagnostic categories such as presence or absence of disease.

Alzheimer’s Disease Neuroimaging Initiative biomarkers as quantitative phenotypes: Genetics core aims, progress, and plans

The role of the Alzheimers Disease Neuroimaging Initiative Genetics Core is to facilitate the investigation of genetic influences on disease onset and trajectory as reflected in structural, functional, and molecular imaging changes; fluid biomarkers; and cognitive status. Major goals include (1) blood sample processing, genotyping, and dissemination, (2) genome‐wide association studies (GWAS) of longitudinal phenotypic data, and (3) providing a central resource, point of contact and planning group for genetics within the Alzheimers Disease Neuroimaging Initiative. Genome‐wide array data have been publicly released and updated, and several neuroimaging GWAS have recently been reported examining baseline magnetic resonance imaging measures as quantitative phenotypes. Other preliminary investigations include copy number variation in mild cognitive impairment and Alzheimers disease and GWAS of baseline cerebrospinal fluid biomarkers and longitudinal changes on magnetic resonance imaging. Blood collection for RNA studies is a new direction. Genetic studies of longitudinal phenotypes hold promise for elucidating disease mechanisms and risk, development of therapeutic strategies, and refining selection criteria for clinical trials.

Association of CR1, CLU and PICALM with Alzheimer's disease in a cohort of clinically characterized and neuropathologically verified individuals

In this study, we assess 34 of the most replicated genetic associations for Alzheimers disease (AD) using data generated on Affymetrix SNP 6.0 arrays and imputed at over 5.7 million markers from a unique cohort of over 1600 neuropathologically defined AD cases and controls (1019 cases and 591 controls). Testing the top genes from the AlzGene meta-analysis, we confirm the well-known association with APOE single nucleotide polymorphisms (SNPs), the CLU, PICALM and CR1 SNPs recently implicated in unusually large data sets, and previously implicated CST3 and ACE SNPs. In the cases of CLU, PICALM and CR1, as well as in APOE, the odds ratios we find are slightly larger than those previously reported in clinical samples, consistent with what we believe to be more accurate classification of disease in the clinically characterized and neuropathologically confirmed AD cases and controls.

Voxelwise genome-wide association study (vGWAS).

The structure of the human brain is highly heritable, and is thought to be influenced by many common genetic variants, many of which are currently unknown. Recent advances in neuroimaging and genetics have allowed collection of both highly detailed structural brain scans and genome-wide genotype information. This wealth of information presents a new opportunity to find the genes influencing brain structure. Here we explore the relation between 448,293 single nucleotide polymorphisms in each of 31,622 voxels of the entire brain across 740 elderly subjects (mean age+/-s.d.: 75.52+/-6.82 years; 438 male) including subjects with Alzheimers disease, Mild Cognitive Impairment, and healthy elderly controls from the Alzheimers Disease Neuroimaging Initiative (ADNI). We used tensor-based morphometry to measure individual differences in brain structure at the voxel level relative to a study-specific template based on healthy elderly subjects. We then conducted a genome-wide association at each voxel to identify genetic variants of interest. By studying only the most associated variant at each voxel, we developed a novel method to address the multiple comparisons problem and computational burden associated with the unprecedented amount of data. No variant survived the strict significance criterion, but several genes worthy of further exploration were identified, including CSMD2 and CADPS2. These genes have high relevance to brain structure. This is the first voxelwise genome wide association study to our knowledge, and offers a novel method to discover genetic influences on brain structure.