Search

African descent populations have a lower Alzheimer disease risk from ApoE ε4 compared to other populations. Ancestry analysis showed that the difference in risk between African and European populations lies in the ancestral genomic background surrounding the ApoE locus (local ancestry). Identifying the mechanism(s) of this protection could lead to greater insight into the etiology of Alzheimer disease and more personalized therapeutic intervention. Our objective is to follow up the local ancestry finding and identify the genetic variants that drive this risk difference and result in a lower risk for developing Alzheimer disease in African ancestry populations. We performed association analyses using a logistic regression model with the ApoE ε4 allele as an interaction term and adjusted for genome-wide ancestry, age, and sex. Discovery analysis included imputed SNP data of 1,850 Alzheimer disease and 4,331 cognitively intact African American individuals. We performed replication analyses on 63 whole genome sequenced Alzheimer disease and 648 cognitively intact Ibadan individuals. Additionally, we reproduced results using whole-genome sequencing of 273 Alzheimer disease and 275 cognitively intact admixed Puerto Rican individuals. A further comparison was done with SNP imputation from an additional 8,463 Alzheimer disease and 11,365 cognitively intact non-Hispanic White individuals. We identified a significant interaction between the ApoE ε4 allele and the SNP rs10423769_A allele, (β = -0.54,SE = 0.12,p-value = 7.50x10-6) in the discovery data set, and replicated this finding in Ibadan (β = -1.32,SE = 0.52,p-value = 1.15x10-2) and Puerto Rican (β = -1.27,SE = 0.64,p-value = 4.91x10-2) individuals. The non-Hispanic Whites analyses showed an interaction trending in the "protective" direction but failing to pass a 0.05 significance threshold (β = -1.51,SE = 0.84,p-value = 7.26x10-2). The presence of the rs10423769_A allele reduces the odds ratio for Alzheimer disease risk from 7.2 for ApoE ε4/ε4 carriers lacking the A allele to 2.1 for ApoE ε4/ε4 carriers with at least one A allele. This locus is located approximately 2 mB upstream of the ApoE locus, in a large cluster of pregnancy specific beta-1 glycoproteins on chromosome 19 and lies within a long noncoding RNA, ENSG00000282943. This study identified a new African-ancestry specific locus that reduces the risk effect of ApoE ε4 for developing Alzheimer disease. The mechanism of the interaction with ApoEε4 is not known but suggests a novel mechanism for reducing the risk for ε4 carriers opening the possibility for potential ancestry-specific therapeutic intervention.

The ApoE ε4 allele is the most significant genetic risk factor for late-onset Alzheimer disease. The risk conferred by ε4, however, differs across populations, with populations of African ancestry showing lower ε4 risk compared to those of European or Asian ancestry. The cause of this heterogeneity in risk effect is currently unknown; it may be due to environmental or cultural factors correlated with ancestry, or it may be due to genetic variation local to the ApoE region that differs among populations. Exploring these hypotheses may lead to novel, population-specific therapeutics and risk predictions. To test these hypotheses, we analyzed ApoE genotypes and genome-wide array data in individuals from African American and Puerto Rican populations. A total of 1,766 African American and 220 Puerto Rican individuals with late-onset Alzheimer disease, and 3,730 African American and 169 Puerto Rican cognitively healthy individuals (> 65 years) participated in the study. We first assessed average ancestry across the genome ("global" ancestry) and then tested it for interaction with ApoE genotypes. Next, we assessed the ancestral background of ApoE alleles ("local" ancestry) and tested if ancestry local to ApoE influenced Alzheimer disease risk while controlling for global ancestry. Measures of global ancestry showed no interaction with ApoE risk (Puerto Rican: p-value = 0.49; African American: p-value = 0.65). Conversely, ancestry local to the ApoE region showed an interaction with the ApoE ε4 allele in both populations (Puerto Rican: p-value = 0.019; African American: p-value = 0.005). ApoE ε4 alleles on an African background conferred a lower risk than those with a European ancestral background, regardless of population (Puerto Rican: OR = 1.26 on African background, OR = 4.49 on European; African American: OR = 2.34 on African background, OR = 3.05 on European background). Factors contributing to the lower risk effect in the ApoE gene ε4 allele are likely due to ancestry-specific genetic factors near ApoE rather than non-genetic ethnic, cultural, and environmental factors.

Improving accuracy in genetic studies would greatly accelerate understanding the genetic basis of complex diseases. One approach to achieve such an improvement for risk variants identified by the genome wide association study (GWAS) approach is to incorporate previously known biology when screening variants across the genome. We developed a simple approach for improving the prioritization of candidate disease genes that incorporates a network diffusion of scores from known disease genes using a protein network and a novel integration with GWAS risk scores, and tested this approach on a large Alzheimer disease (AD) GWAS dataset. Using a statistical bootstrap approach, we cross-validated the method and for the first time showed that a network approach improves the expected replication rates in GWAS studies. Several novel AD genes were predicted including CR2, SHARPIN, and PTPN2. Our re-prioritized results are enriched for established known AD-associated biological pathways including inflammation, immune response, and metabolism, whereas standard non-prioritized results were not. Our findings support a strategy of considering network information when investigating genetic risk factors.

Abstract Background Blood-derived mitochondrial DNA copy number (mtDNA-CN) is a proxy measurement of mitochondrial function in the peripheral and central systems. Abnormal mtDNA-CN not only indicates impaired mtDNA replication and transcription machinery but also dysregulated biological processes such as energy and lipid metabolism. However, the relationship between mtDNA-CN and Alzheimer disease (AD) is unclear. Methods We performed two-sample Mendelian randomization (MR) using publicly available summary statistics from GWAS for mtDNA-CN and AD to investigate the causal relationship between mtDNA-CN and AD. We estimated mtDNA-CN using whole-genome sequence data from blood and brain samples of 13,799 individuals from the Alzheimer’s Disease Sequencing Project. Linear and Cox proportional hazards models adjusting for age, sex, and study phase were used to assess the association of mtDNA-CN with AD. The association of AD biomarkers and serum metabolites with mtDNA-CN in blood was evaluated in Alzheimer’s Disease Neuroimaging Initiative using linear regression. We conducted a causal mediation analysis to test the natural indirect effects of mtDNA-CN change on AD risk through the significantly associated biomarkers and metabolites. Results MR analysis suggested a causal relationship between decreased blood-derived mtDNA-CN and increased risk of AD (OR = 0.68; P = 0.013). Survival analysis showed that decreased mtDNA-CN was significantly associated with higher risk of conversion from mild cognitive impairment to AD (HR = 0.80; P = 0.002). We also identified significant associations of mtDNA-CN with brain FDG-PET (β = 0.103; P = 0.022), amyloid-PET (β = 0.117; P = 0.034), CSF amyloid-β (Aβ) 42/40 (β=-0.124; P = 0.017), CSF t-Tau (β = 0.128; P = 0.015), p-Tau (β = 0.140; P = 0.008), and plasma NFL (β=-0.124; P = 0.004) in females. Several lipid species, amino acids, biogenic amines in serum were also significantly associated with mtDNA-CN. Causal mediation analyses showed that about a third of the effect of mtDNA-CN on AD risk was mediated by plasma NFL (P = 0.009), and this effect was more significant in females (P

The accumulation of amyloid beta (Aβ) peptide (Amyloid cascade hypothesis), an APP protein cleavage product, is a leading hypothesis in the etiology of Alzheimer's disease (AD). In order to identify additional AD risk genes, we performed targeted sequencing and rare variant burden association study for nine candidate genes involved in the amyloid metabolism in 1886 AD cases and 1700 controls. We identified a significant variant burden association for the gene encoding caspase-8, CASP8 (p = 8.6x10-5). For two CASP8 variants, p.K148R and p.I298V, the association remained significant in a combined sample of 10,820 cases and 8,881 controls. For both variants we performed bioinformatics structural, expression and enzymatic activity studies and obtained evidence for loss of function effects. In addition to their role in amyloid processing, caspase-8 and its downstream effector caspase-3 are involved in synaptic plasticity, learning, memory and control of microglia pro-inflammatory activation and associated neurotoxicity, indicating additional mechanisms that might contribute to AD. As caspase inhibition has been proposed as a mechanism for AD treatment, our finding that AD-associated CASP8 variants reduce caspase function calls for caution and is an impetus for further studies on the role of caspases in AD and other neurodegenerative diseases.

Coronary collateral circulation protects cardiac tissues from myocardial infarction damage and decreases sudden cardiac death. So far, it is unclear how coronary collateralization varies by race-ethnicity groups and by sex.We assessed 868 patients with obstructive CAD. Patients were assessed for collateral grades based on Rentrop grading system, as well as other covariates. DNA samples were genotyped using the Affymetrix 6.0 genotyping array. To evaluate genetic contributions to collaterals, we performed admixture mapping using logistic regression with estimated local and global ancestry.Overall, 53% of participants had collaterals. We found difference between sex and racial-ethnic groups. Men had higher rates of collaterals than women (P-value = 0.000175). White Hispanics/Latinos showed overall higher rates of collaterals than African Americans and non-Hispanic Whites (59%, 50% and 48%, respectively, P-value = 0.017), and especially higher rates in grade 1 and grade 3 collateralization than the other two populations (P-value = 0.0257). Admixture mapping showed Native American ancestry was associated with the presence of collaterals at a region on chromosome 17 (chr17:35,243,142-41,251,931, β = 0.55, P-value = 0.000127). African ancestry also showed association with collaterals at a different region on chromosome 17 (chr17: 32,266,966-34,463,323, β = 0.38, P-value = 0.00072).In our study, collateralization showed sex and racial-ethnic differences in obstructive CAD patients. We identified two regions on chromosome 17 that were likely to harbor genetic variations that influenced collateralization.

Alzheimer disease (AD) is the most common cause of dementia. As with many complex diseases, the identified variants do not explain the total expected genetic risk that is based on heritability estimates for AD. Isolated founder populations, such as the Amish, are advantageous for genetic studies as they overcome heterogeneity limitations associated with complex population studies. We determined that Amish AD cases harbored a significantly higher burden of the known risk alleles compared to Amish cognitively normal controls, but a significantly lower burden when compared to cases from a dataset of unrelated individuals. Whole-exome sequencing of a selected subset of the overall study population was used as a screening tool to identify variants located in the regions of the genome that are most likely to contribute risk. By then genotyping the top candidate variants from the known AD genes and from linkage regions implicated previous studies in the full dataset, new associations could be confirmed. The most significant result (p = 0.0012) was for rs73938538, a synonymous variant in LAMA1 within the previously identified linkage peak on chromosome 18. However, this association is specific to the Amish and did not generalize when tested in a dataset of unrelated individuals. These results suggest that additional risk variation in the Amish remains to be identified and likely resides outside of the classical protein coding gene regions.

Alzheimer's disease (AD) and related dementias are a major public health challenge and present a therapeutic imperative for which we need additional insight into molecular pathogenesis. We performed a genome-wide association study and analysis of known genetic risk loci for AD dementia using neuropathologic data from 4,914 brain autopsies. Neuropathologic data were used to define clinico-pathologic AD dementia or controls, assess core neuropathologic features of AD (neuritic plaques, NPs; neurofibrillary tangles, NFTs), and evaluate commonly co-morbid neuropathologic changes: cerebral amyloid angiopathy (CAA), Lewy body disease (LBD), hippocampal sclerosis of the elderly (HS), and vascular brain injury (VBI). Genome-wide significance was observed for clinico-pathologic AD dementia, NPs, NFTs, CAA, and LBD with a number of variants in and around the apolipoprotein E gene (APOE). GalNAc transferase 7 (GALNT7), ATP-Binding Cassette, Sub-Family G (WHITE), Member 1 (ABCG1), and an intergenic region on chromosome 9 were associated with NP score; and Potassium Large Conductance Calcium-Activated Channel, Subfamily M, Beta Member 2 (KCNMB2) was strongly associated with HS. Twelve of the 21 non-APOE genetic risk loci for clinically-defined AD dementia were confirmed in our clinico-pathologic sample: CR1, BIN1, CLU, MS4A6A, PICALM, ABCA7, CD33, PTK2B, SORL1, MEF2C, ZCWPW1, and CASS4 with 9 of these 12 loci showing larger odds ratio in the clinico-pathologic sample. Correlation of effect sizes for risk of AD dementia with effect size for NFTs or NPs showed positive correlation, while those for risk of VBI showed a moderate negative correlation. The other co-morbid neuropathologic features showed only nominal association with the known AD loci. Our results discovered new genetic associations with specific neuropathologic features and aligned known genetic risk for AD dementia with specific neuropathologic changes in the largest brain autopsy study of AD and related dementias.

IntroductionHispanic/Latino populations are underrepresented in Alzheimer Disease (AD) genetic studies. Puerto Ricans (PR), a three-way admixed (European, African, and Amerindian) population is the second-largest Hispanic group in the continental US. We aimed to conduct a genome-wide association study (GWAS) and comprehensive analyses to identify novel AD susceptibility loci and characterize known AD genetic risk loci in the PR population.Materials and methodsOur study included Whole Genome Sequencing (WGS) and phenotype data from 648 PR individuals (345 AD, 303 cognitively unimpaired). We used a generalized linear-mixed model adjusting for sex, age, population substructure, and genetic relationship matrix. To infer local ancestry, we merged the dataset with the HGDP/1000G reference panel. Subsequently, we conducted univariate admixture mapping (AM) analysis.ResultsWe identified suggestive signals within the SLC38A1 and SCN8A genes on chromosome 12q13. This region overlaps with an area of linkage of AD in previous studies (12q13) in independent data sets further supporting. Univariate African AM analysis identified one suggestive ancestral block (p = 7.2×10−6) located in the same region. The ancestry-aware approach showed that this region has both European and African ancestral backgrounds and both contributing to the risk in this region. We also replicated 11 different known AD loci -including APOE- identified in mostly European studies, which is likely due to the high European background of the PR population.ConclusionPR GWAS and AM analysis identified a suggestive AD risk locus on chromosome 12, which includes the SLC38A1 and SCN8A genes. Our findings demonstrate the importance of designing GWAS and ancestry-aware approaches and including underrepresented populations in genetic studies of AD.

BACKGROUND:Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 m genotypes from 25,580 Alzheimer's cases and 48,466 controls. PRINCIPAL FINDINGS:In addition to earlier reported genes, we detected genome-wide significant loci on chromosomes 8 (TP53INP1, p = 1.4×10-6) and 14 (IGHV1-67 p = 7.9×10-8) which indexed novel susceptibility loci. SIGNIFICANCE:The additional genes identified in this study, have an array of functions previously implicated in Alzheimer's disease, including aspects of energy metabolism, protein degradation and the immune system and add further weight to these pathways as potential therapeutic targets in Alzheimer's disease.

Studying population isolates with large, complex pedigrees has many advantages for discovering genetic susceptibility loci; however, statistical analyses can be computationally challenging. Allelic association tests need to be corrected for relatedness among study participants, and linkage analyses require subdividing and simplifying the pedigree structures. We have extended GenomeSIMLA to simulate SNP data in complex pedigree structures based on an Amish pedigree to generate the same structure and distribution of sampled individuals. We evaluated type 1 error rates when no disease SNP was simulated and power when disease SNPs with recessive, additive, and dominant modes of inheritance and odds ratios of 1.1, 1.5, 2.0, and 5.0 were simulated. We generated subpedigrees with a maximum bit-size of 24 using PedCut and performed two-point and multipoint linkage using Merlin. We also ran MQLS on the subpedigrees and unified pedigree. We saw no inflation of type 1 error when running MQLS on either the whole pedigrees or the sub-pedigrees, and we saw low type 1 error for two-point and multipoint linkage. Power was reduced when running MQLS on the subpedigrees versus the whole pedigree, and power was low for two-point and multipoint linkage analyses of the subpedigrees. These data suggest that MQLS has appropriate type 1 error rates in our Amish pedigree structure, and while type 1 error does not seem to be affected when dividing the pedigree prior to linkage analysis, power to detect linkage is diminished when the pedigree is divided.

Alzheimer disease (AD) is a devastating neurodegenerative disease affecting more than five million Americans. In this study, we have used updated genetic linkage data from chromosome 10 in combination with expression data from serial analysis of gene expression to choose a new set of thirteen candidate genes for genetic analysis in late onset Alzheimer disease (LOAD). Results in this study identify the KIAA1462 locus as a candidate locus for LOAD in APOE4 carriers. Two genes exist at this locus, KIAA1462, a gene associated with coronary artery disease, and "rokimi", encoding an untranslated spliced RNA The genetic architecture at this locus suggests that the gene product important in this association is either "rokimi", or a different isoform of KIAA1462 than the isoform that is important in cardiovascular disease. Expression data suggests that isoform f of KIAA1462 is a more attractive candidate for association with LOAD in APOE4 carriers than "rokimi" which had no detectable expression in brain.

To discover susceptibility genes of late-onset Alzheimer's disease (LOAD), we conducted a 3-stage genome-wide association study (GWAS) using three populations: Japanese from the Japanese Genetic Consortium for Alzheimer Disease (JGSCAD), Koreans, and Caucasians from the Alzheimer Disease Genetic Consortium (ADGC). In Stage 1, we evaluated data for 5,877,918 genotyped and imputed SNPs in Japanese cases (n = 1,008) and controls (n = 1,016). Genome-wide significance was observed with 12 SNPs in the APOE region. Seven SNPs from other distinct regions with p-values

Genetic variants that modify brain gene expression may also influence risk for human diseases. We measured expression levels of 24,526 transcripts in brain samples from the cerebellum and temporal cortex of autopsied subjects with Alzheimer's disease (AD, cerebellar n=197, temporal cortex n=202) and with other brain pathologies (non-AD, cerebellar n=177, temporal cortex n=197). We conducted an expression genome-wide association study (eGWAS) using 213,528 cisSNPs within ± 100 kb of the tested transcripts. We identified 2,980 cerebellar cisSNP/transcript level associations (2,596 unique cisSNPs) significant in both ADs and non-ADs (q

Despite the ever-increasing throughput and steadily decreasing cost of next generation sequencing (NGS), whole genome sequencing of humans is still not a viable option for the majority of genetics laboratories. This is particularly true in the case of complex disease studies, where large sample sets are often required to achieve adequate statistical power. To fully leverage the potential of NGS technology on large sample sets, several methods have been developed to selectively enrich for regions of interest. Enrichment reduces both monetary and computational costs compared to whole genome sequencing, while allowing researchers to take advantage of NGS throughput. Several targeted enrichment approaches are currently available, including molecular inversion probe ligation sequencing (MIPS), oligonucleotide hybridization based approaches, and PCR-based strategies. To assess how these methods performed when used in conjunction with the ABI SOLID3+, we investigated three enrichment techniques: Nimblegen oligonucleotide hybridization array-based capture; Agilent SureSelect oligonucleotide hybridization solution-based capture; and Raindance Technologies' multiplexed PCR-based approach. Target regions were selected from exons and evolutionarily conserved areas throughout the human genome. Probe and primer pair design was carried out for all three methods using their respective informatics pipelines. In all, approximately 0.8 Mb of target space was identical for all 3 methods. SOLiD sequencing results were analyzed for several metrics, including consistency of coverage depth across samples, on-target versus off-target efficiency, allelic bias, and genotype concordance with array-based genotyping data. Agilent SureSelect exhibited superior on-target efficiency and correlation of read depths across samples. Nimblegen performance was similar at read depths at 20× and below. Both Raindance and Nimblegen SeqCap exhibited tighter distributions of read depth around the mean, but both suffered from lower on-target efficiency in our experiments. Raindance demonstrated the highest versatility in assay design.

A major goal of personalized medicine is to pre-symptomatically identify individuals at high risk for disease using knowledge of each individual's particular genetic profile and constellation of environmental risk factors. With the identification of several well-replicated risk factors for age-related macular degeneration (AMD), the leading cause of legal blindness in older adults, this previously unreachable goal is beginning to seem less elusive. However, recently developed algorithms have either been much less accurate than expected, given the strong effects of the identified risk factors, or have not been applied to independent datasets, leaving unknown how well they would perform in the population at large. We sought to increase accuracy by using novel modeling strategies, including multifactor dimensionality reduction (MDR) and grammatical evolution of neural networks (GENN), in addition to the traditional logistic regression approach. Furthermore, we rigorously designed and tested our models in three distinct datasets: a Vanderbilt-Miami (VM) clinic-based case-control dataset, a VM family dataset, and the population-based Age-related Maculopathy Ancillary (ARMA) Study cohort. Using a consensus approach to combine the results from logistic regression and GENN models, our algorithm was successful in differentiating between high- and low-risk groups (sensitivity 77.0%, specificity 74.1%). In the ARMA cohort, the positive and negative predictive values were 63.3% and 70.7%, respectively. We expect that future efforts to refine this algorithm by increasing the sample size available for model building, including novel susceptibility factors as they are discovered, and by calibrating the model for diverse populations will improve accuracy.

Parkinson's disease (PD) has had six genome-wide association studies (GWAS) conducted as well as several gene expression studies. However, only variants in MAPT and SNCA have been consistently replicated. To improve the utility of these approaches, we applied pathway analyses integrating both GWAS and gene expression. The top 5000 SNPs (p

Copy number variations (CNVs) are a major cause of genetic disruption in the human genome with far more nucleotides being altered by duplications and deletions than by single nucleotide polymorphisms (SNPs). In the multifaceted etiology of autism spectrum disorders (ASDs), CNVs appear to contribute significantly to our understanding of the pathogenesis of this complex disease. A unique resource of 42 extended ASD families was genotyped for over 1 million SNPs to detect CNVs that may contribute to ASD susceptibility. Each family has at least one avuncular or cousin pair with ASD. Families were then evaluated for co-segregation of CNVs in ASD patients. We identified a total of five deletions and seven duplications in eleven families that co-segregated with ASD. Two of the CNVs overlap with regions on 7p21.3 and 15q24.1 that have been previously reported in ASD individuals and two additional CNVs on 3p26.3 and 12q24.32 occur near regions associated with schizophrenia. These findings provide further evidence for the involvement of ICA1 and NXPH1 on 7p21.3 in ASD susceptibility and highlight novel ASD candidates, including CHL1, FGFBP3 and POUF41. These studies highlight the power of using extended families for gene discovery in traits with a complex etiology.

Genome-wide association studies (GWAS) of late-onset Alzheimer disease (LOAD) have consistently observed strong evidence of association with polymorphisms in APOE. However, until recently, variants at few other loci with statistically significant associations have replicated across studies. The present study combines data on 483,399 single nucleotide polymorphisms (SNPs) from a previously reported GWAS of 492 LOAD cases and 496 controls and from an independent set of 439 LOAD cases and 608 controls to strengthen power to identify novel genetic association signals. Associations exceeding the experiment-wide significance threshold (alpha=1.03x10(-7)) were replicated in an additional 1,338 cases and 2,003 controls. As expected, these analyses unequivocally confirmed APOE's risk effect (rs2075650, P=1.9x10(-36)). Additionally, the SNP rs11754661 at 151.2 Mb of chromosome 6q25.1 in the gene MTHFD1L (which encodes the methylenetetrahydrofolate dehydrogenase (NADP+ dependent) 1-like protein) was significantly associated with LOAD (P=4.70x10(-8); Bonferroni-corrected P=0.022). Subsequent genotyping of SNPs in high linkage disequilibrium (r2>0.8) with rs11754661 identified statistically significant associations in multiple SNPs (rs803424, P=0.016; rs2073067, P=0.03; rs2072064, P=0.035), reducing the likelihood of association due to genotyping error. In the replication case-control set, we observed an association of rs11754661 in the same direction as the previous association at P=0.002 (P=1.90x10(-10) in combined analysis of discovery and replication sets), with associations of similar statistical significance at several adjacent SNPs (rs17349743, P=0.005; rs803422, P=0.004). In summary, we observed and replicated a novel statistically significant association in MTHFD1L, a gene involved in the tetrahydrofolate synthesis pathway. This finding is noteworthy, as MTHFD1L may play a role in the generation of methionine from homocysteine and influence homocysteine-related pathways and as levels of homocysteine are a significant risk factor for LOAD development.

In Northern European descended populations, genetic susceptibility for multiple sclerosis (MS) is associated with alleles of the human leukocyte antigen (HLA) Class II gene DRB1. Whether other major histocompatibility complex (MHC) genes contribute to MS susceptibility is controversial.A case control analysis was performed using 958 single nucleotide polymorphisms (SNPs) spanning the MHC assayed in two independent datasets. The discovery dataset consisted of 1,018 cases and 1,795 controls and the replication dataset was composed of 1,343 cases and 1,379 controls. The most significantly MS-associated SNP in the discovery dataset was rs3135391, a Class II SNP known to tag the HLA-DRB1*15:01 allele, the primary MS susceptibility allele in the MHC (O.R. = 3.04, p < 1 x 10(-78)). To control for the effects of the HLA-DRB1*15:01 haplotype, case control analysis was performed adjusting for this HLA-DRB1*15:01 tagging SNP. After correction for multiple comparisons (false discovery rate = .05) 52 SNPs in the Class I, II and III regions were significantly associated with MS susceptibility in both datasets using the Cochran Armitage trend test. The discovery and replication datasets were merged and subjects carrying the HLA-DRB1*15:01 tagging SNP were excluded. Association tests showed that 48 of the 52 replicated SNPs retained significant associations with MS susceptibility independently of the HLA-DRB1*15:01 as defined by the tagging SNP. 20 Class I SNPs were associated with MS susceptibility with p-values < or = 1 x 10(-8). The most significantly associated SNP was rs4959039, a SNP in the downstream un-translated region of the non-classical HLA-G gene (Odds ratio 1.59, 95% CI 1.40, 1.81, p = 8.45 x 10(-13)) and is in linkage disequilibrium with several nearby SNPs. Logistic regression modeling showed that this SNP's contribution to MS susceptibility was independent of the Class II and Class III SNPs identified in this screen.A MHC Class I locus contributes to MS susceptibility independently of the HLA-DRB1*15:01 haplotype.

Over the next few years, the efficient use of next-generation sequencing (NGS) in human genetics research will depend heavily upon the effective mechanisms for the selective enrichment of genomic regions of interest. Recently, comprehensive exome capture arrays have become available for targeting approximately 33 Mb or approximately 180,000 coding exons across the human genome. Selective genomic enrichment of the human exome offers an attractive option for new experimental designs aiming to quickly identify potential disease-associated genetic variants, especially in family-based studies. We have evaluated a 2.1 M feature human exome capture array on eight individuals from a three-generation family pedigree. We were able to cover up to 98% of the targeted bases at a long-read sequence read depth of > or = 3, 86% at a read depth of > or = 10, and over 50% of all targets were covered with > or = 20 reads. We identified up to 14,284 SNPs and small indels per individual exome, with up to 1,679 of these representing putative novel polymorphisms. Applying the conservative genotype calling approach HCDiff, the average rate of detection of a variant allele based on Illumina 1 M BeadChips genotypes was 95.2% at > or = 10x sequence. Further, we propose an advantageous genotype calling strategy for low covered targets that empirically determines cut-off thresholds at a given coverage depth based on existing genotype data. Application of this method was able to detect >99% of SNPs covered > or = 8x. Our results offer guidance for "real-world" applications in human genetics and provide further evidence that microarray-based exome capture is an efficient and reliable method to enrich for chromosomal regions of interest in next-generation sequencing experiments.

The Alzheimer disease (AD) amyloid protein precursor (APP) can bind the FE65 adaptor protein and this complex can regulate gene expression. We carried out yeast two-hybrid studies with a PTB domain of FE65, focusing on those genes that might be involved in nuclear signaling, and identified and validated Teashirt proteins as FE65 interacting proteins in neurons. Using reporter systems, we observed that FE65 could simultaneously recruit SET, a component of the inhibitor of acetyl transferase, and Teashirt, which in turn recruited histone deacetylases, to produce a powerful gene-silencing complex. We screened stable cell lines with a macroarray focusing on AD-related genes and identified CASP4, encoding caspase-4, as a target of this silencing complex. Chromatin immunoprecipitation showed a direct interaction of FE65 and Teashirt3 with the promoter region of CASP4. Expression studies in postmortem samples demonstrated decreasing expression of Teashirt and increasing expression of caspase-4 with progressive cognitive decline. Importantly, there were significant increases in caspase-4 expression associated with even the earliest neuritic plaque changes in AD. We evaluated a case-control cohort and observed evidence for a genetic association between the Teashirt genes TSHZ1 and TSHZ3 and AD, with the TSHZ3 SNP genotype correlating with expression of Teashirt3. The results were consistent with a model in which reduced expression of Teashirt3, mediated by genetic or other causes, increases caspase-4 expression, leading to progression of AD. Thus the cell biological, gene expression and genetic data support a role for Teashirt/caspase-4 in AD biology. As caspase-4 shows evidence of being a primate-specific gene, current models of AD and other neurodegenerative conditions may be incomplete because of the absence of this gene in the murine genome.

The objective of this study was to determine if MTND2*LHON4917G (4917G), a specific non-synonymous polymorphism in the mitochondrial genome previously associated with neurodegenerative phenotypes, is associated with increased risk for age-related macular degeneration (AMD). A preliminary study of 393 individuals (293 cases and 100 controls) ascertained at Vanderbilt revealed an increased occurrence of 4917G in cases compared to controls (15.4% vs.9.0%, p = 0.11). Since there was a significant age difference between cases and controls in this initial analysis, we extended the study by selecting Caucasian pairs matched at the exact age at examination. From the 1547 individuals in the Vanderbilt/Duke AMD population association study (including 157 in the preliminary study), we were able to match 560 (280 cases and 280 unaffected) on exact age at examination. This study population was genotyped for 4917G plus specific AMD-associated nuclear genome polymorphisms in CFH, LOC387715 and ApoE. Following adjustment for the listed nuclear genome polymorphisms, 4917G independently predicts the presence of AMD (OR = 2.16, 95%CI 1.20-3.91, p = 0.01). In conclusion, a specific mitochondrial polymorphism previously implicated in other neurodegenerative phenotypes (4917G) appears to convey risk for AMD independent of recently discovered nuclear DNA polymorphisms.

The ATP-binding cassette, subfamily A (ABC1), member 7 (ABCA7) gene is associated with Alzheimer’s disease (AD) risk in populations of African, Asian, and European ancestry1-5. Numerous ABCA7 mutations contributing to risk have been identified, including a 44 base pair deletion (rs142076058) specific to individuals of African ancestry and predicted to cause a frameshift mutation (p.Arg578Alafs) (Cukier et al., 2016). The UMi043-A human induced pluripotent stem cell line was derived from an African American individual with AD who is heterozygous for this deletion and is a resource to further investigate ABCA7 and how this African-specific deletion may influence disease pathology.

Abstract One of the core challenges in applying machine learning and artificial intelligence to medicine is the limited availability of annotated medical data. Unlike in other applications of machine learning, where an abundance of labeled data is available, the labeling and annotation of medical data and images require a major effort of manual work by expert clinicians who do not have the time to annotate manually. In this work, we propose a new deep learning technique (SLIVER-net), to predict clinical features from 3-dimensional volumes using a limited number of manually annotated examples. SLIVER-net is based on transfer learning, where we borrow information about the structure and parameters of the network from publicly available large datasets. Since public volume data are scarce, we use 2D images and account for the 3-dimensional structure using a novel deep learning method which tiles the volume scans, and then adds layers that leverage the 3D structure. In order to illustrate its utility, we apply SLIVER-net to predict risk factors for progression of age-related macular degeneration (AMD), a leading cause of blindness, from optical coherence tomography (OCT) volumes acquired from multiple sites. SLIVER-net successfully predicts these factors despite being trained with a relatively small number of annotated volumes (hundreds) and only dozens of positive training examples. Our empirical evaluation demonstrates that SLIVER-net significantly outperforms standard state-of-the-art deep learning techniques used for medical volumes, and its performance is generalizable as it was validated on an external testing set. In a direct comparison with a clinician panel, we find that SLIVER-net also outperforms junior specialists, and identifies AMD progression risk factors similarly to expert retina specialists.

To characterize metabolites and metabolic pathways altered in intermediate and neovascular age-related macular degeneration (IAMD and NVAMD), high resolution untargeted metabolomics was performed via liquid chromatography-mass spectrometry on plasma samples obtained from 91 IAMD patients, 100 NVAMD patients, and 195 controls. Plasma metabolite levels were compared between: AMD patients and controls, IAMD patients and controls, and NVAMD and IAMD patients. Partial least-squares discriminant analysis and linear regression were used to identify discriminatory metabolites. Pathway analysis was performed to determine metabolic pathways altered in AMD. Among the comparisons, we identified 435 unique discriminatory metabolic features. Using computational methods and tandem mass spectrometry, we identified 11 metabolic features whose molecular identities had been previously verified and confirmed the molecular identities of three additional discriminatory features. Included among the discriminatory metabolites were acylcarnitines, phospholipids, amino acids, and steroid metabolites. Pathway analysis revealed that lipid, amino acid, and vitamin metabolism pathways were altered in NVAMD, IAMD, or AMD in general, including the carnitine shuttle pathway which was significantly altered in all comparisons. Finally, few discriminatory features were identified between IAMD patients and controls, suggesting that plasma metabolic profiles of IAMD patients are more similar to controls than to NVAMD patients.