Combinatorial Mismatch Scan (CMS) for loci associated with dementia in the Amish

BACKGROUND: Population heterogeneity may be a significant confounding factor hampering detection and verification of late onset Alzheimer's disease (LOAD) susceptibility genes. The Amish communities located in Indiana and Ohio are relatively isolated populations that may have increased power to detect disease susceptibility genes. METHODS: We recently performed a genome scan of dementia in this population that detected several potential loci. However, analyses of these data are complicated by the highly consanguineous nature of these Amish pedigrees. Therefore we applied the Combinatorial Mismatch Scanning (CMS) method that compares identity by state (IBS) (under the presumption of identity by descent (IBD)) sharing in distantly related individuals from such populations where standard linkage and association analyses are difficult to implement. CMS compares allele sharing between individuals in affected and unaffected groups from founder populations. Comparisons between cases and controls were done using two Fisher's exact tests, one testing for excess in IBS allele frequency and the other testing for excess in IBS genotype frequency for 407 microsatellite markers. RESULTS: In all, 13 dementia cases and 14 normal controls were identified who were not related at least through the grandparental generation. The examination of allele frequencies identified 24 markers (6%) nominally (p ≤ 0.05) associated with dementia; the most interesting (empiric p ≤ 0.005) markers were D3S1262, D5S211, and D19S1165. The examination of genotype frequencies identified 21 markers (5%) nominally (p ≤ 0.05) associated with dementia; the most significant markers were both located on chromosome 5 (D5S1480 and D5S211). Notably, one of these markers (D5S211) demonstrated differences (empiric p ≤ 0.005) under both tests. CONCLUSION: Our results provide the initial groundwork for identifying genes involved in late-onset Alzheimer's disease within the Amish community. Genes identified within this isolated population will likely play a role in a subset of late-onset AD cases across more general populations. Regions highlighted by markers demonstrating suggestive allelic and/or genotypic differences will be the focus of more detailed examination to characterize their involvement in dementia

Exome Sequencing of a Multigenerational Human Pedigree

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 ∼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 ≥3, 86% at a read depth of ≥10, and over 50% of all targets were covered with ≥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 ≥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 ≥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

Analysis of brain region-specific co-expression networks reveals clustering of established and novel genes associated with Alzheimer disease

Background Identifying and understanding the functional role of genetic risk factors for Alzheimer disease (AD) has been complicated by the variability of genetic influences across brain regions and confounding with age-related neurodegeneration. Methods A gene co-expression network was constructed using data obtained from the Allen Brain Atlas for multiple brain regions (cerebral cortex, cerebellum, and brain stem) in six individuals. Gene network analyses were seeded with 52 reproducible (i.e., established) AD (RAD) genes. Genome-wide association study summary data were integrated with the gene co-expression results and phenotypic information (i.e., memory and aging-related outcomes) from gene knockout studies in Drosophila to generate rankings for other genes that may have a role in AD. Results We found that co-expression of the RAD genes is strongest in the cortical regions where neurodegeneration due to AD is most severe. There was significant evidence for two novel AD-related genes including EPS8 (FDR p = 8.77 × 10−3) and HSPA2 (FDR p = 0.245). Conclusions Our findings indicate that AD-related risk factors are potentially associated with brain region-specific effects on gene expression that can be detected using a gene network approach

Ordered subset linkage analysis supports a susceptibility locus for age-related macular degeneration on chromosome 16p12

BACKGROUND: Age-related macular degeneration (AMD) is a complex disorder that is responsible for the majority of central vision loss in older adults living in developed countries. Phenotypic and genetic heterogeneity complicate the analysis of genome-wide scans for AMD susceptibility loci. The ordered subset analysis (OSA) method is an approach for reducing heterogeneity, increasing statistical power for detecting linkage, and helping to define the most informative data set for follow-up analysis. OSA assesses the linkage evidence in subsets of potentially more homogeneous families by rank-ordering family-specific lod scores with respect to trait-associated covariates or phenotypic features. Here, we present results of incorporating five continuous covariates into our genome-wide linkage analysis of 389 microsatellite markers in 62 multiplex families: Body mass index (BMI), systolic (SBP) and diastolic (DBP) blood pressure, intraocular pressure (IOP), and pack-years of cigarette smoking. Chromosome-wide significance of increases in nonparametric multipoint lod scores in covariate-defined subsets relative to the overall sample was assessed by permutation. RESULTS: Using a correction for testing multiple covariates, statistically significant lod score increases were observed for two chromosomal regions: 14q13 with a lod score of 3.2 in 28 families with average IOP ≤ 15.5 (p = 0.002), and 6q14 with a lod score of 1.6 in eight families with average BMI ≥ 30.1 (p = 0.0004). On chromosome 16p12, nominally significant lod score increases (p ≤ 0.05), up to a lod score of 2.9 in 32 families, were observed with several covariate orderings. While less significant, this was the only region where linkage evidence was associated with multiple clinically meaningful covariates and the only nominally significant finding when analysis was restricted to advanced forms of AMD. Families with linkage to 16p12 had higher averages of SBP, IOP and BMI and were primarily affected with neovascular AMD. For all three regions, linkage signals at or very near the peak marker have previously been reported. CONCLUSION: Our results suggest that a susceptibility gene on chromosome 16p12 may predispose to AMD, particularly to the neovascular form, and that further research into the previously suggested association of neovascular AMD and systemic hypertension is warranted

A noise-reduction GWAS analysis implicates altered regulation of neurite outgrowth and guidance in autism

<p>Abstract</p> <p>Background</p> <p>Genome-wide Association Studies (GWAS) have proved invaluable for the identification of disease susceptibility genes. However, the prioritization of candidate genes and regions for follow-up studies often proves difficult due to false-positive associations caused by statistical noise and multiple-testing. In order to address this issue, we propose the novel GWAS noise reduction (GWAS-NR) method as a way to increase the power to detect true associations in GWAS, particularly in complex diseases such as autism.</p> <p>Methods</p> <p>GWAS-NR utilizes a linear filter to identify genomic regions demonstrating correlation among association signals in multiple datasets. We used computer simulations to assess the ability of GWAS-NR to detect association against the commonly used joint analysis and Fisher's methods. Furthermore, we applied GWAS-NR to a family-based autism GWAS of 597 families and a second existing autism GWAS of 696 families from the Autism Genetic Resource Exchange (AGRE) to arrive at a compendium of autism candidate genes. These genes were manually annotated and classified by a literature review and functional grouping in order to reveal biological pathways which might contribute to autism aetiology.</p> <p>Results</p> <p>Computer simulations indicate that GWAS-NR achieves a significantly higher classification rate for true positive association signals than either the joint analysis or Fisher's methods and that it can also achieve this when there is imperfect marker overlap across datasets or when the closest disease-related polymorphism is not directly typed. In two autism datasets, GWAS-NR analysis resulted in 1535 significant linkage disequilibrium (LD) blocks overlapping 431 unique reference sequencing (RefSeq) genes. Moreover, we identified the nearest RefSeq gene to the non-gene overlapping LD blocks, producing a final candidate set of 860 genes. Functional categorization of these implicated genes indicates that a significant proportion of them cooperate in a coherent pathway that regulates the directional protrusion of axons and dendrites to their appropriate synaptic targets.</p> <p>Conclusions</p> <p>As statistical noise is likely to particularly affect studies of complex disorders, where genetic heterogeneity or interaction between genes may confound the ability to detect association, GWAS-NR offers a powerful method for prioritizing regions for follow-up studies. Applying this method to autism datasets, GWAS-NR analysis indicates that a large subset of genes involved in the outgrowth and guidance of axons and dendrites is implicated in the aetiology of autism.</p

SNPs in Multi-Species Conserved Sequences (MCS) as useful markers in association studies: a practical approach

<p>Abstract</p> <p>Background</p> <p>Although genes play a key role in many complex diseases, the specific genes involved in most complex diseases remain largely unidentified. Their discovery will hinge on the identification of key sequence variants that are conclusively associated with disease. While much attention has been focused on variants in protein-coding DNA, variants in noncoding regions may also play many important roles in complex disease by altering gene regulation. Since the vast majority of noncoding genomic sequence is of unknown function, this increases the challenge of identifying "functional" variants that cause disease. However, evolutionary conservation can be used as a guide to indicate regions of noncoding or coding DNA that are likely to have biological function, and thus may be more likely to harbor SNP variants with functional consequences. To help bias marker selection in favor of such variants, we devised a process that prioritizes annotated SNPs for genotyping studies based on their location within Multi-species Conserved Sequences (MCSs) and used this process to select SNPs in a region of linkage to a complex disease. This allowed us to evaluate the utility of the chosen SNPs for further association studies. Previously, a region of chromosome 1q43 was linked to Multiple Sclerosis (MS) in a genome-wide screen. We chose annotated SNPs in the region based on location within MCSs (termed MCS-SNPs). We then obtained genotypes for 478 MCS-SNPs in 989 individuals from MS families.</p> <p>Results</p> <p>Analysis of our MCS-SNP genotypes from the 1q43 region and comparison to HapMap data confirmed that annotated SNPs in MCS regions are frequently polymorphic and show subtle signatures of selective pressure, consistent with previous reports of genome-wide variation in conserved regions. We also present an online tool that allows MCS data to be directly exported to the UCSC genome browser so that MCS-SNPs can be easily identified within genomic regions of interest.</p> <p>Conclusion</p> <p>Our results showed that MCS can easily be used to prioritize markers for follow-up and candidate gene association studies. We believe that this novel approach demonstrates a paradigm for expediting the search for genes contributing to complex diseases.</p

Association of mitochondrial variants and haplogroups identified by whole exome sequencing with Alzheimer's disease

Introduction: Findings regarding the association between mitochondrial DNA (mtDNA) variants and Alzheimer's disease (AD) are inconsistent. Methods: We developed a pipeline for accurate assembly and variant calling in mitochondrial genomes embedded within whole exome sequences (WES) from 10,831 participants from the Alzheimer's Disease Sequencing Project (ADSP). Association of AD risk was evaluated with each mtDNA variant and variants located in 1158 nuclear genes related to mitochondrial function using the SCORE test. Gene-based tests were performed using SKAT-O. Results: Analysis of 4220 mtDNA variants revealed study-wide significant association of AD with a rare MT-ND4L variant (rs28709356 C&gt;T; minor allele frequency = 0.002; P = 7.3 × 10 −5) as well as with MT-ND4L in a gene-based test (P = 6.71 × 10 −5). Significant association was also observed with a MT-related nuclear gene, TAMM41, in a gene-based test (P = 2.7 × 10 −5). The expression of TAMM41 was lower in AD cases than controls (P =.00046) or mild cognitive impairment cases (P =.03). Discussion: Significant findings in MT-ND4L and TAMM41 provide evidence for a role of mitochondria in AD.</p

Clinical and genetic heterogeneity in familial focal segmental glomerulosclerosis

Clinical and genetic heterogeneity in familial focal segmental glomerulosclerosis.BackgroundFamilial forms of focal segmental glomerulosclerosis (FFSGS) that exhibit autosomal dominant or recessive patterns of inheritance have been described. The genetic basis of these hereditary forms of FSGS is unknown. One recent study of a kindred from Oklahoma with an autosomal dominant form of FSGS linked this disease to a region of chromosome 19q. In addition, polymorphisms in a gene in this region on chromosome 19q13 have been linked to congenital nephrotic syndrome of the Finnish type. We have ascertained and characterized a large family with autosomal dominant FFSGS (Duke 6530).MethodsFamilies were compared for clinical and genetic heterogeneity. To test for linkage of our family to this portion of chromosome 19, genomic DNA was isolated from 102 family members, and polymerase chain reaction was performed using eight microsatellite markers that spanned the area of interest on chromosome 19. Data were evaluated using two-point linkage analysis, multipoint analysis, and an admixture test.ResultsLinkage was excluded at a distance of ±5 to 10cm for all markers tested with two-point log10 of the odds of linkage (LOD) scores and from an approximate 60cm interval in this area of chromosome 19q via multipoint analysis.ConclusionFSGS has been called the “final common pathway” of glomerular injury, as it is a frequent pathological manifestation with diverse etiologies. This diversity likely correlates with the genetic heterogeneity that we have established. Thus, our data demonstrate that there are at least two genes responsible for this disease, and there is genetic as well as clinical heterogeneity in autosomal dominant FSGS

Linkage analyses in Caribbean Hispanic families identify novel loci associated with familial late-onset Alzheimer's disease

INTRODUCTION: We performed linkage analyses in Caribbean Hispanic families with multiple late-onset Alzheimer's disease (LOAD) cases to identify regions that may contain disease causative variants. METHODS: We selected 67 LOAD families to perform genome-wide linkage scan. Analysis of the linked regions was repeated using the entire sample of 282 families. Validated chromosomal regions were analyzed using joint linkage and association. RESULTS: We identified 26 regions linked to LOAD (HLOD ≥3.6). We validated 13 of the regions (HLOD ≥2.5) using the entire family sample. The strongest signal was at 11q12.3 (rs2232932: HLODmax = 4.7, Pjoint = 6.6 × 10(-6)), a locus located ∼2 Mb upstream of the membrane-spanning 4A gene cluster. We additionally identified a locus at 7p14.3 (rs10255835: HLODmax = 4.9, Pjoint = 1.2 × 10(-5)), a region harboring genes associated with the nervous system (GARS, GHRHR, and NEUROD6). DISCUSSION: Future sequencing efforts should focus on these regions because they may harbor familial LOAD causative mutations

Targeted massively parallel sequencing of autism spectrum disorder-associated genes in a case control cohort reveals rare loss-of-function risk variants

BACKGROUND: Autism spectrum disorder (ASD) is highly heritable, yet genome-wide association studies (GWAS), copy number variation screens, and candidate gene association studies have found no single factor accounting for a large percentage of genetic risk. ASD trio exome sequencing studies have revealed genes with recurrent de novo loss-of-function variants as strong risk factors, but there are relatively few recurrently affected genes while as many as 1000 genes are predicted to play a role. As such, it is critical to identify the remaining rare and low-frequency variants contributing to ASD. METHODS: We have utilized an approach of prioritization of genes by GWAS and follow-up with massively parallel sequencing in a case-control cohort. Using a previously reported ASD noise reduction GWAS analyses, we prioritized 837 RefSeq genes for custom targeting and sequencing. We sequenced the coding regions of those genes in 2071 ASD cases and 904 controls of European white ancestry. We applied comprehensive annotation to identify single variants which could confer ASD risk and also gene-based association analysis to identify sets of rare variants associated with ASD. RESULTS: We identified a significant over-representation of rare loss-of-function variants in genes previously associated with ASD, including a de novo premature stop variant in the well-established ASD candidate gene RBFOX1. Furthermore, ASD cases were more likely to have two damaging missense variants in candidate genes than controls. Finally, gene-based rare variant association implicates genes functioning in excitatory neurotransmission and neurite outgrowth and guidance pathways including CACNAD2, KCNH7, and NRXN1. CONCLUSIONS: We find suggestive evidence that rare variants in synaptic genes are associated with ASD and that loss-of-function mutations in ASD candidate genes are a major risk factor, and we implicate damaging mutations in glutamate signaling receptors and neuronal adhesion and guidance molecules. Furthermore, the role of de novo mutations in ASD remains to be fully investigated as we identified the first reported protein-truncating variant in RBFOX1 in ASD. Overall, this work, combined with others in the field, suggests a convergence of genes and molecular pathways underlying ASD etiology. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13229-015-0034-z) contains supplementary material, which is available to authorized users