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We conducted a meta-analysis of Parkinson's disease genome-wide association studies using a common set of 7,893,274 variants across 13,708 cases and 95,282 controls. Twenty-six loci were identified as having genome-wide significant association; these and 6 additional previously reported loci were then tested in an independent set of 5,353 cases and 5,551 controls. Of the 32 tested SNPs, 24 replicated, including 6 newly identified loci. Conditional analyses within loci showed that four loci, including GBA, GAK-DGKQ, SNCA and the HLA region, contain a secondary independent risk variant. In total, we identified and replicated 28 independent risk variants for Parkinson's disease across 24 loci. Although the effect of each individual locus was small, risk profile analysis showed substantial cumulative risk in a comparison of the highest and lowest quintiles of genetic risk (odds ratio (OR) = 3.31, 95% confidence interval (CI) = 2.55-4.30; P = 2 × 10−16). We also show six risk loci associated with proximal gene expression or DNA methylation. [ABSTRACT FROM AUTHOR]

We performed an exome-wide association analysis in 1393 late-onset Alzheimer’s disease (LOAD) cases and 8141 controls from the CHARGE consortium. We found that a rare variant (P155L) in TM2D3 was enriched in Icelanders (~0.5% versus <0.05% in other European populations). In 433 LOAD cases and 3903 controls from the Icelandic AGES sub-study, P155L was associated with increased risk and earlier onset of LOAD [odds ratio (95% CI) = 7.5 (3.5–15.9), p = 6.6x10-9]. Mutation in the Drosophila TM2D3 homolog, almondex, causes a phenotype similar to loss of Notch/Presenilin signaling. Human TM2D3 is capable of rescuing these phenotypes, but this activity is abolished by P155L, establishing it as a functionally damaging allele. Our results establish a rare TM2D3 variant in association with LOAD susceptibility, and together with prior work suggests possible links to the β-amyloid cascade.

During aging, intracranial volume remains unchanged and represents maximally attained brain size, while various interacting biological phenomena lead to brain volume loss. Consequently, intracranial volume and brain volume in late life reflect different genetic influences. Our genome-wide association study (GWAS) in 8,175 community-dwelling elderly persons did not reveal any associations at genome-wide significance (P < 5 × 10?8) for brain volume. In contrast, intracranial volume was significantly associated with two loci: rs4273712 (P = 3.4 × 10?11), a known height-associated locus on chromosome 6q22, and rs9915547 (P = 1.5 × 10?12), localized to the inversion on chromosome 17q21. We replicated the associations of these loci with intracranial volume in a separate sample of 1,752 elderly persons (P = 1.1 × 10?3 for 6q22 and 1.2 × 10?3 for 17q21). Furthermore, we also found suggestive associations of the 17q21 locus with head circumference in 10,768 children (mean age of 14.5 months). Our data identify two loci associated with head size, with the inversion at 17q21 also likely to be involved in attaining maximal brain size. [ABSTRACT FROM AUTHOR]

Objective: Genome-wide association (GWAS) methods have identified genes contributing to Parkinson's disease (PD); we sought to identify additional genes associated with PD susceptibility. Methods: A 2-stage design was used. First, individual level genotypic data from 5 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 single-nucleotide polymorphisms (SNPs) were genotyped in an independent Replication Sample (3,738 cases and 2,111 controls). Results: 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 human leukocyte antigen (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. Interpretation: We identified a novel PD susceptibility locus, RIT2, replicated several previously identified loci, and identified more than 1 risk allele within SNCA and GBA.ANN NEUROL 2012; [ABSTRACT FROM AUTHOR]

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<5x10-8) association with disease risk: BST1, CCDC62/HIP1R, DGKQ/GAK, GBA, LRRK2, MAPT, MCCC1/LAMP3,P A R K 1 6 , SNCA, STK39,a n d SYT11/RAB25. In addition, we identified novel evidence for genome-wide significant association with a polymorphism in ITGA8 (rs7077361, OR 0.88, P=1.3x10-8). 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. [ABSTRACT FROM AUTHOR]

Mutations in the leucine-rich repeat kinase 2 gene, located at 12q12, are the most common known genetic causes of Parkinson's disease. Studies of leucine-rich repeat kinase 2 mutation carriers have shown incomplete and age-dependent penetrance, and previous studies have suggested that inherited susceptibility factors may modify the penetrance of leucine-rich repeat kinase 2 mutations. Genomewide linkage to age of onset of leucine-rich repeat kinase 2-related Parkinson's disease was evaluated in a sample of 113 leucine-rich repeat kinase 2 mutation carriers from 64 families using single-nucleotide polymorphism data from the Illumina HumanCNV370 genotyping array. Association between onset age and single-nucleotide polymorphisms under suggestive linkage peaks was also evaluated. The top logarithmic odds score for onset age (logarithmic odds score = 2.43) was in the chromosome 1q32.1 region. Moderate linkage to onset was also identified at 16q12.1 (logarithmic odds score = 1.58). Examination of single-nucleotide polymorphism association to Parkinson's disease onset under the linkage peaks revealed no statistically significant single-nucleotide polymorphism associations. The 2 novel genomic regions identified may harbor modifiers of leucine-rich repeat kinase 2-related Parkinson's disease onset age or penetrance, and further study of these regions may provide important insight into leucine-rich repeat kinase 2-related Parkinson's disease. © 2011 Movement Disorder Society [ABSTRACT FROM AUTHOR]

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 Illumina 370Duo 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 realtime 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 [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This article discusses a study which identified additional loci associated with late-onset Alzheimer's disease (AD). White participants in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) criteria served as subjects in this study. The study compared prevalent cases in the CHARGE cohorts with controls free of dementia at the deoxyribonucleic (DNA) draw date. Results of the study showed that 973 dementia-free individuals developed incident AD over an average follow-up period of eight years. Included is a chart showing the genetic loci at which single-nucleotide polymorphisms (SNPs) associated with AD.

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. [ABSTRACT FROM AUTHOR]

Background: Mutations within the amyloid precursor protein (APP), presenilin‐1 (PSEN1), and presenilin‐2 (PSEN2) genes are known to cause familial Alzheimer's disease (AD). Our goal is to examine the distribution of clinical variants in these genes within the ethnically diverse participants in the Alzheimer Disease Sequencing Project (ADSP) whole genome sequence (N = 4789) and whole exome sequencing (N = 20,158) data. Method: We aggregated mutations reported in APP, PSEN1, and PSEN2 from the Alzheimer's disease and Frontotemporal Dementia Mutation Database, ClinVar, and the Online Mendelian Inheritance in Man, and selected rare variants (minor allele frequency < 1%) described as pathogenic and related to AD or dementia yielding 304 variants (53 in APP, 233 in PSEN1, 18 in PSEN2). We counted the presence of these clinically implicated variants in the currently available ADSP data. Result: Among 22,558 ADSP subjects passing quality control filters we observed 16 PSEN1, 5 PSEN2 and 6 APP variants. We identified 48 individuals (13 controls, 30 AD cases, 5 missing AD diagnosis) that were heterozygous for one of these variants. An additional AD case was a compound heterozygote for two APP variants. Out of the total sample, 0.06% of African Americans (AA), 0.21% of whites (non‐Hispanic white or white with ethnicity unknown), and 0.33% of Hispanics (HI) were carriers. In contrast, AA, white, and HI represented 21%, 63%, and 15% of the sample, respectively. The carriers included two pairs of second‐degree relatives: one Hispanic pair and one pair consisting of one Hispanic and one white/ethnicity unknown individual. Conclusion: A reported mutation in APP, PSEN1 or PSEN2 was observed in 0.22% of ADSP participants, with the lowest carrier rate in AA. Studies in other diseases indicate that disparities in inclusion in genomic sequencing may result in misclassification or higher rate of uncertain significance for patients in underrepresented populations (e.g. Manrai et.al. 2016, Spratt et.al. 2016). It is unknown if the current difference in observed carrier rate by ancestry reflects study design, a true difference in frequency of AD causal APP, PSEN1, and PSEN2 mutations across populations, or limitations in identified pathogenic mutations due to populations historically included in genetic studies of AD. [ABSTRACT FROM AUTHOR]

Background: Using sequencing from multi‐ethnic AD studies, the ADSP aims to identify genomic variation contributing to elevated risk of, or protection from, AD. We examined coding region variation in the ADSP WES (whole exome sequencing) Release 2 dataset, comprising jointly‐called genotypes on 12,135 non‐Hispanic White (NHW), 4,108 African American (AA), and 2,159 Hispanic (HI) samples, to characterize ethnic differences and similarities in AD risk profiles across 40 known AD susceptibility loci. Method: The ADSP WES Release 2 dataset includes genotype data on 8,789 cases and 9,613 controls collected in nine datasets using 10 target capture kits jointly called by the Genomic Center for Alzheimer's Disease (GCAD). To test genetic associations, we first combined genotype data that had been QCed (quality‐controlled) by 'subset' of source dataset and capture kit, excluded low quality variants and samples, and then stratified by race/ethnicity. Within race/ethnicity, we performed association analyses with the package GENESIS, accounting for relatedness and population substructure, with covariate adjustment for QC subset. Result: In preliminary analyses of 6,572,710 coding region variants, only APOE region associations attained genome‐wide significance (P < 5 × 10−8) across strata. Examining 20 AD loci with coding region associations in two prior exome analyses (Sims et al. 2017 and Bis et al. 2019) and/or a recent large GWAS of AD (Kunkle et al. 2019), different variants demonstrated nominal associations (P < 0.05) in TREM2 across ethnicities (NHW, rs75932628, P < 10−40; AA, rs2234255, P = 2.56 × 10−3; HI, rs115953314, P = 1.30 × 10−4). No other variant/gene was associated across all ethnicities, though ethnicity‐specific association patterns were observed at two genes among NHW and AA, but not HI: ABI3 (NHW, 16:81910580:A:G, P = 4.7 × 10−4; AA, rs374229872, P = 5.61 × 10−3) and PLCG2 (NHW, rs142527437, P = 2.45 × 10−3; AA, rs35031462, P = 0.01). Analyses of NHW revealed strong associations at AC099552.4 (rs1043915, P = 0.0039) and PILRA (7:155196965:G:A, P = 1.0 × 10−5), and among HI, a modest association was observed at LDB3 (rs76615432, P = 0.01). Analyses examining co‐localization of coding region signals across strata using ethnicity‐specific LD structure are on‐going and will be reported. Conclusion: NHW and AA share associations in previously identified AD genes: TREM2, ABI3, and PLCG2. Other genes demonstrated suggestive ethnicity‐specific associations, but work is on‐going to determine if these reflect true ethnic differences. [ABSTRACT FROM AUTHOR]

Background: Genome‐wide association studies (GWAS) of brain volumes have identified common genetic variants with modest effect sizes that lie mainly in non‐coding regions. We sought to identify low frequency and rare variants influencing brain volumes by performing whole genome association analyses using sequence data from the Trans‐Omics for Precision Medicine (TOPMed) Program. Methods: We analyzed up to 3,975 participants (58% women; 78% Europeans, 22% African‐Americans), mean age of 62.5 (13.9), from four TOPMed population‐ or family‐based studies (FHS, GENESTAR, CHS, and GENOA). We excluded participants with dementia, stroke, presence of large brain infarcts, tumor or any other finding affecting the scan. We tested the association of hippocampal (HV), total brain (TBV), lateral ventricular (LVV) and intracranial (ICV) volumes with individual genetic variants using mixed‐effect linear regression models adjusted for age, age2, sex, study and principal components. Models including HV, TBV and LVV were adjusted for ICV. We accounted for relatedness using a kinship matrix and trait variance variability using a random effects model. We retained variants with a minor allele count greater than 40. Results: We detected new genome‐wide significant (P < 5 × 10−8) low frequency or rare variants in five regions associated with HV (5q31, P = 10−9) and TBV (2p22, P = 10−8; 17q25, P = 4 × 10−9; Xp11, P = 2 × 10−10; Xq21, P = 4 × 10−8). We also confirmed previously observed common variants in GWAS loci for HV (12q14 & 12q24), LVV (3q28, 12q23 & 16q24) and ICV (6q21, 6q22 & 17q21). The top 5q31 hit for HV (rs246587) lies at 19kb from the PCDHAC2 gene, encoding neural cadherin‐like cell adhesion proteins that most likely play a critical role in the establishment and maintenance of specific neuronal connections in the brain. Conclusions: Our whole genome analysis revealed intriguing new loci associated with brain volumes. Future work will include ancestry‐specific and conditional analyses, gene‐based and burden tests as well as the inclusion of additional TOPMed cohorts. Supported by: U01s AG058589, AG052409, R01s AG054076, AG033040 AG049607, HL112064, NS062059, FHS contracts HHSN268201500001I and 75N92019D00031, R01HL131136 (Analysis Commons). [ABSTRACT FROM AUTHOR]

Background: Biobanks provide great resources for genetic association analysis. To increase power of genetic association analysis, we propose a novel approach to exploit family history of disease that is often available in biobanks. While methods have been proposed to incorporate family history in single variant analysis, methods to incorporate this information in gene‐based tests, such as the Sequence kernel association test (SKAT), are not available. The goal of this project is to develop a familial history aggregation‐based test (FHAT) to improve power to detect rare variant associations in gene‐based tests, and to apply this method to detect genes associated with Alzheimer's Disease (AD). Method: We assume that participants' genotypes, and phenotypes of participants' and their relatives, such as parents, are available from a large cohort. We first assess the association between participants' genotypes and their phenotypes. Then we evaluate the association between participants' genotypes and a set of relatives' disease status conditional on the participants' disease status. We use a weighted meta‐analysis to combing the score statistics from probands and their relatives. We evaluate the FHAT in simulations, and we apply our novel method to detect associations of gene regions with Alzheimer's Disease (AD) in the UK Biobank data incorporating parental disease history. Result: Our simulation results showed that the type I error of FHAT is well controlled with disease prevalence of 10% and 20%. We obtained corrected type I error rate at various alpha levels using 10,000 simulation replicates with a sample size of 5,000. Out of seven genes previously implicated in AD susceptibility, six showed evidence of association using FHAT in UK Biobank. These six genes had improved significance after incorporating parental phenotype information. Conclusion: We proposed a novel approach to include family history, as is often available from medical charts, and showed improved power to detect aggregates of rare variant genetic associations with AD in large cohorts or biobanks. [ABSTRACT FROM AUTHOR]

Background: The PARK2 gene at 6q26 encodes parkin, whose inactivation is implicated in an early-onset autosomal recessive form of Parkinson disease (PD). Objective: To evaluate the influence of heterozygosity for parkin mutation on onset age in a sample of families with at least 2 PD-affected members. Design: Clinical and genetic study. Setting: Twenty collaborative clinical sites. Patients: Patients with familial PD collected in the GenePD study. Studied families were selected for (1) affected sibling pairs sharing 2 alleles identical by state at PARK2 (D6S305) or (2) 1 or more family members with onset age younger than 54 years, regardless of D6S305 status. At least 1 member from each of 183 families underwent comprehensive screening for deletion/insertion variants and point mutations in PARK2. Main Outcome Measures: Mutations in the parkin gene were screened by means of single-stranded conformation polymorphism and sequencing in all 12 coding exons and flanking intronic sequences for point mutations and duplex quantitative polymerase chain reaction in all exons for rearrangement, duplication, and deletion. Results: Mutations were found in 23 families (12.6% of those screened). Among the mutation-positive families, 10 (43%) contained compound heterozygotes; 3 (13%), homozygotes; and 10 (43%), heterozygotes. The onset age in patients with parkin gene mutations ranged from 20 to 76 years. Patients with 1 parkin mutation had an 11.7-year age at onset than did patients with none (P=.04), and patients with 2 or more parkin mutations had a 13.2-year decrease in age at onset compared with patients with 1 mutation (P = .04). Conclusions: These data indicate that parkin mutations are not rare in multiply affected sibships, and that heterozygous mutation carrier status in PARK2 significantly influences age at onset of PD. [ABSTRACT FROM AUTHOR]

The Haplotype Relative Risk (HRR) was first proposed [Falk et al., Ann Hum Genet 1987] to test for Linkage Disequilibrium (LD) between a marker and a putative disease locus using case-parent trios. Spurious association does not appear in such family-based studies under population admixture. In this paper, we extend the HRR to accommodate incomplete trios via the Expectation-Maximization (EM) algorithm [Dempster et al., J R Stat Soc Ser B, 1977]. In addition to triads and dyads (parent-offspring pair), the EM-HRR easily incorporates individuals with no parental genotype information available, which is excluded from the one parent Transmission/Disequilibrium Test (1-TDT) [Sun et al., Am J Epidemiol 1999]. Due to the data structure of EM-HRR, transmitted alleles are always available regardless of the number of missing parental genotypes. As a result of having a larger sample size, computer simulations reveal that the EM-HRR is more powerful in detecting LD than the 1-TDT in a population under Hardy-Weinberg Equilibirum (HWE). If admixture is not extreme, the EM-HRR remains more powerful. When a large degree of admixture exists, the EM-HRR performs better the 1-TDT when the association is strong, though not as well when the association is weak. We illustrate the proposed method with an application to the Framingham Heart Study. Copyright © 2005 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Background: We explored three approaches to heritability and linkage analyses of longitudinal total cholesterol levels (CHOL) in the Genetic Analysis Workshop 13 simulated data without knowing the answers. The first two were univariate approaches and used 1) baseline measure at exam one or 2) summary measures such as mean and slope from multiple exams. The third method was a multivariate approach that directly models multiple measurements on a subject. A variance components model (SOLAR) was employed in the univariate approaches. A mixed regression model with polynomials was employed in the multivariate approach and implemented in SAS/IML. Results: Using the baseline measure at exam 1, we detected all baseline or slope genes contributing a substantial amount (0.08) of variance (LOD > 3). Compared to the baseline measure, the mean measures yielded slightly higher LOD at the slope genes, and a lower LOD at the baseline genes. The slope measure produced a somewhat lower LOD for the slope gene than did the mean measure. Descriptive information on the pattern of changes in gene effects with age was estimated for three linked loci by the third approach. Conclusion: We found simple univariate methods may be effective to detect genes affecting longitudinal phenotypes but may not fully reveal temporal trends in gene effects. The relative efficiency of the univariate methods to detect genes depends heavily on the underlying model. Compared with the univariate approaches, the multivariate approach provided more information on temporal trends in gene effects at the cost of more complicated modelling and more intense computations. [ABSTRACT FROM AUTHOR]

Genome-wide association studies often emphasize single-nucleotide polymorphisms with the smallest p-values with less attention given to single-nucleotide polymorphisms not ranked near the top. We suggest that gene pathways contain valuable information that can enable identification of additional associations. We used gene set information to identify disease-related pathways using three methods: gene set enrichment analysis (GSEA), empirical enrichment p-values, and Ingenuity pathway analysis (IPA). Association tests were performed for common single-nucleotide polymorphisms and aggregated rare variants with traits Q1 and Q4. These pathway methods were evaluated by type I error, power, and the ranking of the VEGF pathway, the gene set used in the simulation model. GSEA and IPA had high power for detecting the VEGF pathway for trait Q1 (91.2% and 93%, respectively). These two methods were conservative with deflated type I errors (0.0083 and 0.0072, respectively). The VEGF pathway ranked 1 or 2 in 123 of 200 replicates using IPA and ranked among the top 5 in 114 of 200 replicates for GSEA. The empirical enrichment method had lower power and higher type I error. Thus pathway analysis approaches may be useful in identifying biological pathways that influence disease outcomes.

Background: 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. Methods: 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. Results: 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.Conclusion Taken together, these results suggest an influence of genes involved in endocytosis and lysosomal sorting in PD pathogenesis.

Background: We report age-dependent penetrance estimates for leucine-rich repeat kinase 2 (LRRK2)-related Parkinson's disease (PD) in a large sample of familial PD. The most frequently seen LRRK2 mutation, Gly2019Ser (G2019S), is associated with approximately 5 to 6% of familial PD cases and 1 to 2% of idiopathic cases, making it the most common known genetic cause of PD. Studies of the penetrance of LRRK2 mutations have produced a wide range of estimates, possibly due to differences in study design and recruitment, including in particular differences between samples of familial PD versus sporadic PD. Methods: A sample, including 903 affected and 58 unaffected members from 509 families ascertained for having two or more PD-affected members, 126 randomly ascertained PD patients and 197 controls, was screened for five different LRRK2 mutations. Penetrance was estimated in families of LRRK2 carriers with consideration of the inherent bias towards increased penetrance in a familial sample. Results: Thirty-one out of 509 families with multiple cases of PD (6.1%) were found to have 58 LRRK2 mutation carriers (6.4%). Twenty-nine of the 31 families had G2019S mutations while two had R1441C mutations. No mutations were identified among controls or unaffected relatives of PD cases. Nine PD-affected relatives of G2019S carriers did not carry the LRRK2 mutation themselves. At the maximum observed age range of 90 to 94 years, the unbiased estimated penetrance was 67% for G2019S families, compared with a baseline PD risk of 17% seen in the non-LRRK2-related PD families. Conclusion: Lifetime penetrance of LRRK2 estimated in the unascertained relatives of multiplex PD families is greater than that reported in studies of sporadically ascertained LRRK2 cases, suggesting that inherited susceptibility factors may modify the penetrance of LRRK2 mutations. In addition, the presence of nine PD phenocopies in the LRRK2 families suggests that these susceptibility factors may also increase the risk of non-LRRK2-related PD. No differences in penetrance were found between men and women, suggesting that the factors that influence penetrance for LRRK2 carriers are independent of the factors which increase PD prevalence in men.

Background: We have increasing information on the role of certain genetic variants in a wide variety of molecular traits and endophenotypes of Alzheimer's disease (AD), but their impacts on the prioritization of AD risk gene are unknown. Method: Based on the summary statistics of the genome‐wide association study (GWAS) of AD published by the International Genomics of Alzheimer's Project (IGAP) consortium (Kunkle et al., 2019), we have weighted each SNP by their associations with traits of eQTL (RNA expression), mQTL (DNA methylation), haQTL (histone acetylation), brain phosphorylated tangles (TAU), β‐amyloid protein (Aβ), and cognitive decline derived from the ROS‐MAP samples of postmortem dorsal‐lateral prefrontal cortex of AMP‐AD. Then, we collapsed all of the weighted SNPs found in each gene using the SKATO test, based on the 1000 reference genome. Result: 38∼43% of genes (n = 12,899) have an increase in their statistical significance level after incorporating the weights of their genetic effects on omic molecular traits and AD endophenotypes. A subset of these gene‐level assessments reach the trait‐specific Bonferroni corrected genome‐wide significance threshold (P < 0.05/number of genes for each trait). The burden of TAU pathology has the strongest effect with RASGRF2, FCF1, ZCWPW1, C6orf10, VAC14, ADGRF2, ACP2, DDB2, and CR1L being prioritized. Similarly, we have results prioritized by weighting by (1) Amyloid β: FCF1, NRXN1, PLCB1, and DLG2; (2) cognitive decline: AKAP13, CR1L, KIAA1671, and CR2; and (3) eQTL: TRIT1, RAPSN, and C6orf10. The latter also emerges from the haQTL analysis, and no results emerge from the mQTL analysis. Conclusion: Weighting by omic molecular traits and endophenotypes leading to AD is able to prioritize additional genes that could contribute to AD susceptibility. Functional validation is ongoing. [ABSTRACT FROM AUTHOR]