Although twin, family, and adoption studies have shown that general cognitive ability (GCA) is substantially heritable, GWAS has not uncovered a genetic polymorphism replicably associated with this phenotype. However, most polymorphisms used in GWAS are common SNPs. The present study explores use of a different class of genetic variant, the copy-number variant (CNV), to predict GCA in a sample of 6,199 participants, combined from two longitudinal family studies. We aggregated low-frequency (<5%) CNV calls into eight different mutational burden scores, each reflecting a different operationalization of mutational burden. We further conducted three genome-wide association scans, each of which utilized a different subset of identified low-frequency CNVs. Association signals from the burden analyses were generally small in effect size, and none were statistically significant after a careful Type I error correction was applied. No signal from the genome-wide scans significantly differed from zero at the adjusted Type I error rate. Thus, the present study provides no evidence that CNVs underlie heritable variance in GCA, though we cannot rule out the possibility of very rare or small-effect CNVs for this trait, which would require even larger samples to detect. We interpret these null results in light of recent breakthroughs that aggregate SNP effects to explain much, but not all, of the heritable variance in some quantitative traits.
Molecular genetics; copy-number variants; CNVs; general cognitive ability; IQ
The distribution of fungiform papillae density and associated factors were examined in the Beaver Dam Offspring Study. Data were from 2371 participants (mean age = 48.8 years, range = 21–84 years) with 1108 males and 1263 females. Fungiform papillae were highlighted with blue food coloring and the number of fungiform papillae within a standard 6-mm circle was counted. Whole mouth suprathreshold taste intensity was measured. The mean fungiform papillae density was 103.5 papillae/cm2 (range = 0–212.2 papillae/cm2). For each 5-year increase in age, the mean fungiform papillae density was 2.8 papillae/cm2 lower and the mean density for males was 10.2 papillae/cm2 lower than for females. Smokers had significantly lower mean densities (former smokers: −5.1 papillae/cm2; current smokers: −9.3 papillae/cm2) than nonsmokers, and heavy alcohol drinkers had a mean density that was 4.7 papillae/cm2 lower than nonheavy drinkers. Solvent exposure was related to a significantly higher density (+6.8 papillae/cm2). The heritability estimate for fungiform papillae density was 40.2%. Propylthiouracil taster status, TAS2R38 haplotype, and perceived taste intensity were not related to density. In summary, wide variability in fungiform papillae density was observed and a number of related factors were found including the modifiable factors of smoking and alcohol consumption.
fungiform papillae; heritability; taste
Olfactory impairment is associated with cognitive impairment in older adults but less is known about the association of olfactory impairment and cognitive function in middle-aged adults. The association between olfactory impairment and cognitive function tests of attention, processing speed and executive and psychomotor function was explored in 2837 participants (21–84 years; mean age 49 years) in the Beaver Dam Offspring Study. Among middle-aged participants (aged 35–64 years), those with impairment on an odor identification test took significantly longer to complete the Trail Making Test (TMT-A and TMT-B) and the Grooved Peg Board (GPB) test, than those without olfactory impairment in regression models adjusted for multiple factors. Similar results were found for the TMT-A and TMT-B, but not the GPB, in the whole cohort. Olfactory impairment was associated with poorer performance on cognitive function tests in a primarily middle-aged cohort.
Olfaction; Odor Identification; Cognitive Function; Executive Function; Epidemiology
Venous thromboembolism (VTE) is a common, heritable disease resulting in
high rates of hospitalization and mortality. Yet few associations between VTE
and genetic variants, all in the coagulation pathway, have been established. To
identify additional genetic determinants of VTE, we conducted a 2-stage
genome-wide association study (GWAS) among individuals of European ancestry in
the extended CHARGE VTE consortium. The discovery GWAS comprised 1,618 incident
VTE cases out of 44,499 participants from six community-based studies. Genotypes
for genome-wide single-nucleotide polymorphisms (SNPs) were imputed to
~2.5 million SNPs in HapMap and association with VTE assessed using
study-design appropriate regression methods. Meta-analysis of these results
identified two known loci, in F5 and ABO. Top
1,047 tag SNPs (p≤0.0016) from the discovery GWAS were tested for
association in an additional 3,231 cases and 3,536 controls from three
case-control studies. In the combined data from these two stages, additional
genome-wide significant associations were observed on 4q35 at
F11 (top SNP rs4253399, intronic to F11)
and on 4q28 at FGG (rs6536024, 9.7 kb from
FGG) (p<5.0×10−13 for both).
The associations at the FGG locus were not completely explained
by previously reported variants. Loci at or near SUSD1 and
OTUD7A showed borderline yet novel associations
(p<5.0×10-6) and constitute new candidate genes. In
conclusion, this large GWAS replicated key genetic associations in
F5 and ABO, and confirmed the importance
of F11 and FGG loci for VTE. Future studies
are warranted to better characterize the associations with F11
and FGG and to replicate the new candidate associations.
venous thrombosis; genetics; genome-wide association; genetic epidemiology
While mutations in glucocerebrosidase (GBA1) are associated with an increased risk for Parkinson disease (PD), it is important to establish whether such mutations are also a common risk factor for other Lewy body disorders.
To establish whether GBA1 mutations are a risk factor for dementia with Lewy bodies (DLB).
We compared genotype data on patients and controls from 11 centers. Data concerning demographics, age at onset, disease duration, and clinical and pathological features were collected when available. We conducted pooled analyses using logistic regression to investigate GBA1 mutation carrier status as predicting DLB or PD with dementia status, using common control subjects as a reference group. Random-effects meta-analyses were conducted to account for additional heterogeneity.
Eleven centers from sites around the world performing genotyping.
Seven hundred twenty-one cases met diagnostic criteria for DLB and 151 had PD with dementia. We compared these cases with 1962 controls from the same centers matched for age, sex, and ethnicity.
Main Outcome Measures
Frequency of GBA1 mutations in cases and controls.
We found a significant association between GBA1 mutation carrier status and DLB, with an odds ratio of 8.28 (95% CI, 4.78–14.88). The odds ratio for PD with dementia was 6.48 (95% CI, 2.53–15.37). The mean age at diagnosis of DLB was earlier in GBA1 mutation carriers than in noncarriers (63.5 vs 68.9 years; P<.001), with higher disease severity scores.
Conclusions and Relevance
Mutations in GBA1 are a significant risk factor for DLB. GBA1 mutations likely play an even larger role in the genetic etiology of DLB than in PD, providing insight into the role of glucocerebrosidase in Lewy body disease.
Genome-wide association (GWAS) methods have identified genes contributing to Parkinson disease (PD); we sought to identify additional genes associated with PD susceptibility.
A two stage design was used. First, individual level genotypic data from five recent PD GWAS (Discovery Sample: 4,238 PD cases and 4,239 controls) were combined. Following imputation, a logistic regression model was employed in each dataset to test for association with PD susceptibility and results from each dataset were meta-analyzed. Second, 768 SNPs were genotyped in an independent Replication Sample (3,738 cases and 2,111 controls).
Genome-wide significance was reached for SNPs in SNCA (rs356165, G: odds ratio (OR)=1.37; p=9.3 × 10−21), MAPT (rs242559, C: OR=0.78; p=1.5 × 10−10), GAK/DGKQ (rs11248051, T:OR=1.35; p=8.2 × 10−9/ rs11248060, T: OR=1.35; p=2.0×10−9), and the HLA region (rs3129882, A: OR=0.83; p=1.2 × 10−8), which were previously reported. The Replication Sample confirmed the associations with SNCA, MAPT, and the HLA region and also with GBA (E326K OR=1.71; p=5 × 10−8 Combined Sample) (N370 OR=3.08; p=7 × 10−5 Replication sample). A novel PD susceptibility locus, RIT2, on chromosome 18 (rs12456492; p=5 × 10−5 Discovery Sample; p=1.52 × 10−7 Replication sample; p=2 × 10−10 Combined Sample) was replicated. Conditional analyses within each of the replicated regions identified distinct SNP associations within GBA and SNCA, suggesting that there may be multiple risk alleles within these genes.
We identified a novel PD susceptibility locus, RIT2, replicated several previously identified loci, and identified more than one risk allele within SNCA and GBA.
Mutations in the leucine-rich repeat kinase 2 gene (LRRK2), located at 12q12, are the most common known genetic causes of Parkinson’s disease (PD). Studies of LRRK2 mutation carriers have shown incomplete and age-dependent penetrance and previous studies have suggested that inherited susceptibility factors may modify the penetrance of LRRK2 mutations.
Genomewide linkage to age of onset of LRRK2-related PD was evaluated in a sample of 113 LRRK2 mutation carriers from 64 families using single nucleotide polymorphism data from the Illumina HumanCNV370 genotyping array. Association between onset age and SNPs located under suggestive linkage peaks was also evaluated.
The top LOD-score for onset age (LOD-score=2.43) was located in the chromosome 1q32.1 region. Moderate linkage to onset was also identified at 16q12.1 (LOD-score=1.58). Examination of single nucleotide polymorphism association to PD onset under the linkage peaks revealed no statistically significant SNP associations.
The two novel genomic regions identified may harbor modifiers of LRRK2-related PD onset age or penetrance and further study of these regions may provide important insight into LRRK2-related PD.
Parkinson’s Disease; LRRK2; Linkage
Whole gene duplications and triplications of alpha-synuclein (SNCA) can cause Parkinson’s disease (PD), and variation in the promoter region (Rep1) and 3′ region of SNCA has been reported to increase disease susceptibility. Within our cohort, one affected individual from each of 92 multiplex PD families showing the greatest evidence of linkage to the region around SNCA was screened for dosage alterations and sequence changes; no dosage or non-synonymous sequence changes were found. In addition, 737 individuals (from 450 multiplex PD families) that met strict diagnostic criteria for PD and did not harbor a known causative mutation, as well as 359 neurologically normal controls, were genotyped for the Rep1 polymorphism and four SNPs in the 3′ region of SNCA. The four SNPs were in high LD (r2 > 0.95) and were analyzed as a haplotype. The effects of the Rep1 genotype and the 3′ haplotype were evaluated using regression models employing only one individual per family. Cases had a 3% higher frequency of the Rep1 263 bp allele compared with controls (OR = 1.54; empirical P-value = 0.02). There was an inverse linear relationship between the number of 263 bp alleles and age of onset (empirical P-value = 0.0004). The 3′ haplotype was also associated with disease (OR = 1.29; empirical P-value = 0.01), but not age of onset (P = 0.40). These data suggest that dosage and sequence changes are a rare cause of PD, but variation in the promoter and 3′ region of SNCA convey an increased risk for PD.
Parkinson’s disease; alpha-synuclein; dosage; Rep1; association
Parkinson disease (PD) is a complex neurodegenerative disorder with largely unknown genetic mechanisms. While the degeneration of dopaminergic neurons in PD mainly takes place in the substantia nigra pars compacta (SN) region, other brain areas, including the prefrontal cortex, develop Lewy bodies, the neuropathological hallmark of PD. We generated and analyzed expression data from the prefrontal cortex Brodmann Area 9 (BA9) of 27 PD and 26 control samples using the 44K One-Color Agilent 60-mer Whole Human Genome Microarray. All samples were male, without significant Alzheimer disease pathology and with extensive pathological annotation available. 507 of the 39,122 analyzed expression probes were different between PD and control samples at false discovery rate (FDR) of 5%. One of the genes with significantly increased expression in PD was the forkhead box O1 (FOXO1) transcription factor. Notably, genes carrying the FoxO1 binding site were significantly enriched in the FDR–significant group of genes (177 genes covered by 189 probes), suggesting a role for FoxO1 upstream of the observed expression changes. Single-nucleotide polymorphisms (SNPs) selected from a recent meta-analysis of PD genome-wide association studies (GWAS) were successfully genotyped in 50 out of the 53 microarray brains, allowing a targeted expression–SNP (eSNP) analysis for 52 SNPs associated with PD affection at genome-wide significance and the 189 probes from FoxO1 regulated genes. A significant association was observed between a SNP in the cyclin G associated kinase (GAK) gene and a probe in the spermine oxidase (SMOX) gene. Further examination of the FOXO1 region in a meta-analysis of six available GWAS showed two SNPs significantly associated with age at onset of PD. These results implicate FOXO1 as a PD–relevant gene and warrant further functional analyses of its transcriptional regulatory mechanisms.
Parkinson disease (PD) is a neurodegenerative disease, which impairs the motor and cognitive abilities of affected individuals. Although the involvement of specific genes in the disease process has been recognized, the underlying genetic mechanisms are not yet understood. One common investigation approach for PD has been the comparison of gene expression levels in brain tissue from PD cases with those from neurologically healthy controls. We performed such an expression analysis in prefrontal cortex tissue from a set of 27 PD and 26 control samples. One of the 489 differentially expressed genes, forkhead box O1 (FOXO1), is involved in transcriptional regulation. Notably, the set of differentially expressed genes identified in our study was enriched for genes regulated by the FoxO1 protein. Analyses of DNA sequence variants known as single-nucleotide polymorphisms (SNPs) in the FOXO1 region, as well as of PD–relevant SNPs across the genome, suggest functional connections between this gene and 1) the age at onset in PD, and 2) the spermine oxidase (SMOX) gene. These findings implicate the involvement of FOXO1 in PD pathogenesis.
Imaging traits provide a powerful and biologically relevant substrate to examine the influence of genetics on the brain. Interest in genome-wide, brain-wide search for influential genetic variants is growing, but has mainly focused on univariate, SNP-based association tests. Moving to gene-based multivariate statistics, we can test the combined effect of multiple genetic variants in a single test statistic. Multivariate models can reduce the number of statistical tests in gene-wide or genome-wide scans and may discover gene effects undetectable with SNP-based methods. Here we present a gene-based method for associating the joint effect of single nucleotide polymorphisms (SNPs) in 18,044 genes across 31,662 voxels of the whole brain in 731 elderly subjects (mean age: 75.56 ± 6.82SD years; 430 males) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Structural MRI scans were analyzed using tensor-based morphometry (TBM) to compute 3D maps of regional brain volume differences compared to an average template image based on healthy elderly subjects. Using the voxel-level volume difference values as the phenotype, we selected the most significantly associated gene (out of 18,044) at each voxel across the brain. No genes identified were significant after correction for multiple comparisons, but several known candidates were re-identified, as were other genes highly relevant to brain function. GAB2, which has been previously associated with late-onset AD, was identified as the top gene in this study, suggesting the validity of the approach. This multivariate, gene-based voxelwise association study offers a novel framework to detect genetic influences on the brain.
principal components regression; voxelwise; multivariate; gene-based; GWAS; GAB2 (max. 6 keywords)
More than 800 published genetic association studies have implicated dozens of potential risk loci in Parkinson's disease (PD). To facilitate the interpretation of these findings, we have created a dedicated online resource, PDGene, that comprehensively collects and meta-analyzes all published studies in the field. A systematic literature screen of ∼27,000 articles yielded 828 eligible articles from which relevant data were extracted. In addition, individual-level data from three publicly available genome-wide association studies (GWAS) were obtained and subjected to genotype imputation and analysis. Overall, we performed meta-analyses on more than seven million polymorphisms originating either from GWAS datasets and/or from smaller scale PD association studies. Meta-analyses on 147 SNPs were supplemented by unpublished GWAS data from up to 16,452 PD cases and 48,810 controls. Eleven loci showed genome-wide significant (P<5×10−8) association with disease risk: BST1, CCDC62/HIP1R, DGKQ/GAK, GBA, LRRK2, MAPT, MCCC1/LAMP3, PARK16, SNCA, STK39, and SYT11/RAB25. In addition, we identified novel evidence for genome-wide significant association with a polymorphism in ITGA8 (rs7077361, OR 0.88, P = 1.3×10−8). All meta-analysis results are freely available on a dedicated online database (www.pdgene.org), which is cross-linked with a customized track on the UCSC Genome Browser. Our study provides an exhaustive and up-to-date summary of the status of PD genetics research that can be readily scaled to include the results of future large-scale genetics projects, including next-generation sequencing studies.
The genetic basis of Parkinson's disease is complex, i.e. it is determined by a number of different disease-causing and disease-predisposing genes. Especially the latter have proven difficult to find, evidenced by more than 800 published genetic association studies, typically showing discrepant results. To facilitate the interpretation of this large and continuously increasing body of data, we have created a freely available online database (“PDGene”: http://www.pdgene.org) which provides an exhaustive account of all published genetic association studies in PD. One particularly useful feature is the calculation and display of up-to-date summary statistics of published data for overlapping DNA sequence variants (polymorphisms). These meta-analyses revealed eleven gene loci that showed a statistically very significant (P<5×10−8; a.k.a. genome-wide significance) association with risk for PD: BST1, CCDC62/HIP1R, DGKQ/GAK, GBA, LRRK2, MAPT, MCCC1/LAMP3, PARK16, SNCA, STK39, SYT11/RAB25. In addition and purely by data-mining, we identified one novel PD susceptibility locus in a gene called ITGA8 (rs7077361, P = 1.3×10−8). We note that our continuously updated database represents the most comprehensive research synopsis of genetic association studies in PD to date. In addition to vastly facilitating the work of other PD geneticists, our approach may serve as a valuable example for other complex diseases.
Genetic Analysis Workshop 17 (GAW17) provided a platform for evaluating existing statistical genetic methods and for developing novel methods to analyze rare variants that modulate complex traits. In this article, we present an overview of the 1000 Genomes Project exome data and simulated phenotype data that were distributed to GAW17 participants for analyses, the different issues addressed by the participants, and the process of preparation of manuscripts resulting from the discussions during the workshop.
Copy number variants (CNVs) are known to cause Mendelian forms of Parkinson disease (PD), most notably in SNCA and PARK2. PARK2 has a recessive mode of inheritance; however, recent evidence demonstrates that a single CNV in PARK2 (but not a single missense mutation) may increase risk for PD. We recently performed a genome-wide association study for PD that excluded individuals known to have either a LRRK2 mutation or two PARK2 mutations. Data from the Illumina370Duo arrays were re-clustered using only white individuals with high quality intensity data, and CNV calls were made using two algorithms, PennCNV and QuantiSNP. After quality assessment, the final sample included 816 cases and 856 controls. Results varied between the two CNV calling algorithms for many regions, including the PARK2 locus (genome-wide p = 0.04 for PennCNV and p = 0.13 for QuantiSNP). However, there was consistent evidence with both algorithms for two novel genes, USP32 and DOCK5 (empirical, genome-wide p-values<0.001). PARK2 CNVs tended to be larger, and all instances that were molecularly tested were validated. In contrast, the CNVs in both novel loci were smaller and failed to replicate using real-time PCR, MLPA, and gel electrophoresis. The DOCK5 variation is more akin to a VNTR than a typical CNV and the association is likely caused by artifact due to DNA source. DNA for all the cases was derived from whole blood, while the DNA for all controls was derived from lymphoblast cell lines. The USP32 locus contains many SNPs with low minor allele frequency leading to a loss of heterozygosity that may have been spuriously interpreted by the CNV calling algorithms as support for a deletion. Thus, only the CNVs within the PARK2 locus could be molecularly validated and associated with PD susceptibility.
Copy number variants (CNVs) are DNA sequence alterations, resulting in gains (duplications) and losses (deletions) of genomic segments. They often overlap genes and may play important roles in disease. Only one published study has examined CNVs in late-onset Alzheimer's disease (AD), and none have examined mild cognitive impairment (MCI). CNV calls were generated in 288 AD, 183 MCI, and 184 healthy control (HC) non-Hispanic Caucasian Alzheimer's Disease Neuroimaging Initiative participants. After quality control, 222 AD, 136 MCI, and 143 HC participants were entered into case/control association analyses, including candidate gene and whole genome approaches. Although no excess CNV burden was observed in cases (AD and/or MCI) relative to controls (HC), gene-based analyses revealed CNVs overlapping the candidate gene CHRFAM7A, as well as CSMD1, SLC35F2, HNRNPCL1, NRXN1, and ERBB4 regions, only in cases. Replication in larger samples is important, after which regions detected here may be promising targets for resequencing.
Late-onset Alzheimer's disease (LOAD) is the most common form of dementia in the elderly. The National Institute of Aging-Late Onset Alzheimer's Disease Family Study and the National Cell Repository for Alzheimer's Disease conducted a joint genome-wide association study (GWAS) of multiplex LOAD families (3,839 affected and unaffected individuals from 992 families plus additional unrelated neurologically evaluated normal subjects) using the 610 IlluminaQuad panel. This cohort represents the largest family-based GWAS of LOAD to date, with analyses limited here to the European-American subjects. SNPs near APOE gave highly significant results (e.g., rs2075650, p = 3.2×10−81), but no other genome-wide significant evidence for association was obtained in the full sample. Analyses that stratified on APOE genotypes identified SNPs on chromosome 10p14 in CUGBP2 with genome-wide significant evidence for association within APOE ε4 homozygotes (e.g., rs201119, p = 1.5×10−8). Association in this gene was replicated in an independent sample consisting of three cohorts. There was evidence of association for recently-reported LOAD risk loci, including BIN1 (rs7561528, p = 0.009 with, and p = 0.03 without, APOE adjustment) and CLU (rs11136000, p = 0.023 with, and p = 0.008 without, APOE adjustment), with weaker support for CR1. However, our results provide strong evidence that association with PICALM (rs3851179, p = 0.69 with, and p = 0.039 without, APOE adjustment) and EXOC3L2 is affected by correlation with APOE, and thus may represent spurious association. Our results indicate that genetic structure coupled with ascertainment bias resulting from the strong APOE association affect genome-wide results and interpretation of some recently reported associations. We show that a locus such as APOE, with large effects and strong association with disease, can lead to samples that require appropriate adjustment for this locus to avoid both false positive and false negative evidence of association. We suggest that similar adjustments may also be needed for many other large multi-site studies.
Genetic factors are well-established to play a role in risk of Alzheimer's disease (AD). However, it has been difficult to find genes that are involved in AD susceptibility, other than a small number of genes that play a role in early-onset, high-penetrant disease risk, and the APOE ε4 allele, which increases risk of late-onset disease. Here we use a European-American family-based sample to examine the role of common genetic variants on late-onset AD. We show that variants in CUGBP2 on chromosome 10p, along with nearby variants, are associated with AD in those highest-risk APOE ε4 homozygotes. We have replicated this interaction in an independent sample. CUGBP2 has one isoform that is expressed predominantly in neurons, and identification of such a new risk locus is important because of the severity of AD. We also provide support for recently proposed associated variants (BIN1, CLU, and partly CR1) and show that there are markers throughout the genome that are correlated with APOE. This emphasizes the need to adjust for APOE for such markers to avoid false associations and suggests that there may be confounding for other diseases with similar strong risk loci.
A genome-wide, whole brain approach to investigate genetic effects on neuroimaging phenotypes for identifying quantitative trait loci is described. The Alzheimer's 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.
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 Alzheimer's disease, Mild Cognitive Impairment, and healthy elderly controls from the Alzheimer's 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.
In a genome-wide association study of structural brain degeneration, we mapped the 3D profile of temporal lobe volume differences in 742 brain MRI scans of Alzheimer’s disease patients, mildly impaired, and healthy elderly subjects. After searching 546,314 genomic markers, 2 single nucleotide polymorphisms (SNPs) were associated with bilateral temporal lobe volume (P < 5×10−7). One SNP, rs10845840, is located in the GRIN2B gene which encodes the N-Methyl-D-Aspartate (NMDA) glutamate receptor NR2B subunit. This protein - involved in learning and memory, and excitotoxic cell death - has age-dependent prevalence in the synapse and is already a therapeutic target in Alzheimer’s disease. Risk alleles for lower temporal lobe volume at this SNP were significantly over-represented in AD and MCI subjects versus controls (odds ratio = 1.273; P = 0.039) and were associated with the mini-mental state exam (MMSE; t = −2.114; P = 0.035) demonstrating a negative effect on global cognitive function. Voxelwise maps of genetic association of this SNP with regional brain volumes, revealed intense temporal lobe effects (FDR correction at q = 0.05; critical P = 0.0257). This study uses large-scale brain mapping for gene discovery with implications for Alzheimer’s disease.
Depression is one of the most common nonmotor complications of Parkinson's disease (PD) and has a major impact on quality of life. Although several clinical factors have been associated with depression in PD, the relationship between depression and stage of illness as well as between depression and degree of disability remains controversial. We have collected clinical data on 1,378 PD cases from 632 families, using the Unified Parkinson's Disease Rating Scale (UPDRS) Parts II (activities of daily living) & III (motor), the Mini-Mental State Exam, the Geriatric Depression Scale (GDS), and the Blessed Functional Activity Scale (Blessed). Analyses were performed using the 840 individuals with verified PD and without evidence of cognitive decline. Logistic regression was used to identify study variables that individually and collectively best predicted the presence of depressive symptoms (GDS ≥ 10). After correcting for multiple tests, depressive symptoms were significantly associated with Hoehn and Yahr stage and other clinical measures but not with any genetic variant (parkin, LRRK2, APOE). The Blessed score, education, presence of a first degree relative with signs of depression, and UPDRS Part II were found to best predict depressive symptomatology (R2 = 0.33; P = 4 × 10−48). Contrary to several reports, the results from this large study indicate that stage of illness, motor impairment, and functional disability are strongly correlated with depressive symptoms.
Parkinson's disease; depression; Hoehn and Yahr stage; association; activities of daily living
Mitochondrial function is impaired in Parkinson's disease (PD) and may contribute to the pathogenesis of PD, but the causes of mitochondrial impairment in PD are unknown. Mitochondrial dysfunction is recapitulated in cell lines expressing mitochondrial DNA (mtDNA) from PD patients, implicating mtDNA variants or mutations, though the role of mtDNA variants or mutations in PD risk remains unclear. We investigated the potential contribution of mtDNA variants or mutations to the risk of PD.
We examined the possibility of a maternal inheritance bias as well as the association between mitochondrial haplogroups and maternal inheritance and disease risk in a case-control study of 168 multiplex PD families in which the proband and one parent were diagnosed with PD. 2-tailed Fisher Exact Tests and McNemar's tests were used to compare allele frequencies, and a t-test to compare ages of onset.
The frequency of affected mothers of the proband with PD (83/167, 49.4%) was not significantly different from the frequency of affected females of the proband generation (115/259, 44.4%) (Odds Ratio 1.22; 95%CI 0.83 - 1.81). After correcting for multiple tests, there were no significant differences in the frequencies of mitochondrial haplogroups or of the 10398G complex I gene polymorphism in PD patients compared to controls, and no significant associations with age of onset of PD. Mitochondrial haplogroup and 10398G polymorphism frequencies were similar in probands having an affected father as compared to probands having an affected mother.
These data fail to demonstrate a bias towards maternal inheritance in familial PD. Consistent with this, we find no association of common haplogroup-defining mtDNA variants or for the 10398G variant with the risk of PD. However, these data do not exclude a role for mtDNA variants in other populations, and it remains possible that other inherited mitochondrial DNA variants, or somatic mDNA mutations, contribute to the risk of familial PD.
Five genes have been identified that contribute to Mendelian forms of Parkinson disease (PD); however, mutations have been found in fewer than 5% of patients, suggesting that additional genes contribute to disease risk. Unlike previous studies that focused primarily on sporadic PD, we have performed the first genomewide association study (GWAS) in familial PD. Genotyping was performed with the Illumina HumanCNV370Duo array in 857 familial PD cases and 867 controls. A logistic model was employed to test for association under additive and recessive modes of inheritance after adjusting for gender and age. No result met genomewide significance based on a conservative Bonferroni correction. The strongest association result was with SNPs in the GAK/DGKQ region on chromosome 4 (additive model: p = 3.4 × 10−6; OR = 1.69). Consistent evidence of association was also observed to the chromosomal regions containing SNCA (additive model: p = 5.5 × 10−5; OR = 1.35) and MAPT (recessive model: p = 2.0 × 10−5; OR = 0.56). Both of these genes have been implicated previously in PD susceptibility; however, neither was identified in previous GWAS studies of PD. Meta-analysis was performed using data from a previous case–control GWAS, and yielded improved p values for several regions, including GAK/DGKQ (additive model: p = 2.5 × 10−7) and the MAPT region (recessive model: p = 9.8 × 10−6; additive model: p = 4.8 × 10−5). These data suggest the identification of new susceptibility alleles for PD in the GAK/DGKQ region, and also provide further support for the role of SNCA and MAPT in PD susceptibility.
After performing a genome-wide association study, it is often difficult to know which regions to follow up, especially when no one marker reaches genome-wide significance. Researchers frequently focus on their top N findings, knowing that true associations may be buried deeper in the list. Others focus on genes or regions that have multiple markers showing evidence of association. However, these markers are often in high linkage disequilibrium with one another (r2 > 0.80), which indicates that these additional markers are providing redundant information. I propose a novel method that identifies regions with multiple lines of evidence, by down-weighting the contribution of additional markers in proportion to pairwise linkage disequilibrium. I have used this non-redundant summary score in my analysis of the North American Rheumatoid Arthritis Consortium dataset released as part of Genetic Analysis Workshop 16. Three regions were identified that had a genome-wide empirical p-value less than 0.01, including one novel region on chromosome 20 near the KCNB1 and PTGIS genes.
Age at onset in Parkinson disease (PD) is a highly heritable quantitative trait for which a significant genetic influence is supported by multiple segregation analyses. Because genes associated with onset age may represent invaluable therapeutic targets to delay the disease, we sought to identify such genetic modifiers using a genomewide association study in familial PD. There have been previous genomewide association studies (GWAS) to identify genes influencing PD susceptibility, but this is the first to identify genes contributing to the variation in onset age.
Initial analyses were performed using genotypes generated with the Illumina HumanCNV370Duo array in a sample of 857 unrelated, familial PD cases. Subsequently, a meta-analysis of imputed SNPs was performed combining the familial PD data with that from a previous GWAS of 440 idiopathic PD cases. The SNPs from the meta-analysis with the lowest p-values and consistency in the direction of effect for onset age were then genotyped in a replication sample of 747 idiopathic PD cases from the Parkinson Institute Biobank of Milan, Italy.
Meta-analysis across the three studies detected consistent association (p < 1 × 10-5) with five SNPs, none of which reached genomewide significance. On chromosome 11, the SNP with the lowest p-value (rs10767971; p = 5.4 × 10-7) lies between the genes QSER1 and PRRG4. Near the PARK3 linkage region on chromosome 2p13, association was observed with a SNP (rs7577851; p = 8.7 × 10-6) which lies in an intron of the AAK1 gene. This gene is closely related to GAK, identified as a possible PD susceptibility gene in the GWAS of the familial PD cases.
Taken together, these results suggest an influence of genes involved in endocytosis and lysosomal sorting in PD pathogenesis.
Mutations in DJ-1 (PARK7) are one cause of early-onset autosomal-recessive parkinsonism. We screened for DJ-1 mutations in 93 affected individuals from the 64 multiplex Parkinson disease (PD) families in our sample that had the highest family-specific multipoint LOD scores at the DJ-1 locus. In addition to sequencing all coding exons for alterations, we used multiplex ligation-dependent probe amplification (MLPA) to examine the genomic copy number of DJ-1 exons. A known polymorphism (R98Q) was found in five PD subjects, once as a homozygote and in the other four cases as heterozygotes. No additional missense mutations and no exon deletions or duplications were detected. Our results, in combination with those of previous studies, suggest that alterations in DJ-1 are not a common cause of familial PD.
Parkinson disease; DJ-1; multiplex ligation-dependent probe amplification; MLPA
The simulated data set of the Genetic Analysis Workshop 15 provided affection status, four quantitative traits, and a covariate. After studying the relationship between these variables, linkage analysis was undertaken. Analyses were performed in the first replicate only and without any prior knowledge of the underlying model. In addition to the main effect of the DR locus on chromosome 6, significant linkage was also identified on chromosomes 8, 9, 11, and 18. Notably, the power to detect linkage increased after transforming the skewed and kurtotic IgM and anti-CCP distributions. Moreover, genes on chromosome 11 could not be discerned from noise without the transformation, thus highlighting the need in real life situations for careful examination of the phenotypic data prior to genetic analysis. Significant association with one single-nucleotide polymorphism was identified for the regions on chromosome 11 and 18. Haplotype analyses were attempted for the other regions, but only the underlying variation of the DR locus could be identified. Two methods were then applied to predict classification using the factors identified so far. These methods – logistic regression and multifactor dimensionality reduction (MDR) – performed comparably for this data set. Those affected individuals that were misclassified as unaffected were then used in a genome-wide association analysis to identify additional susceptibility loci. Two additional loci were identified in this fashion, illustrating the usefulness of this two-stage classification approach.