An autosome-wide search using longitudinal data for loci linked to type 2 diabetes progression

A genome-wide screen was conducted for type 2 diabetes progression genes using measures of elevated fasting glucose levels as quantitative traits from the offspring enrolled in the Framingham Heart Study. We analyzed young (20–34 years) and old (≥ 35 years) subjects separately, using single-point and multipoint sibpair analysis, because of the possible differential impact of progression on the groups of interest. We observed significant linkage with change in fasting glucose levels on 1q25-32 (p = 5.21 × 10(-8)), 3p26.3-21.31 (p = 1 × 10(-11)), 8q23.1-24.13 (p = 2.94 × 10(-6)), 9p24.1-21.3 (p = 7 × 10(-7)), and 18p11.31-q22.1 (p < 10(-11)). The evidence for linkage on chromosomes 8 and 18 was consistent for the subset of study participants aged 43 through 55 years

Optimizing the evidence for linkage by permuting marker order

We developed a new marker-reordering algorithm to find the best order of fine-mapping markers for multipoint linkage analysis. The algorithm searches for the best order of fine-mapping markers such that the sum of the squared differences in identity-by-descent distribution between neighboring markers is minimized. To test this algorithm, we examined its effect on the evidence for linkage in the simulated and the Collaborative Studies on Genetics of Alcoholism (COGA) data. We found enhanced evidence for linkage with the reordered map at the true location in the simulated data (p-value decreased from 1.16 × 10(-9 )to 9.70 × 10(-10)). Analysis of the White population from the COGA data with the reordered map for alcohol dependence led to a significant change of the linkage signal (p = 0.0365 decreased to p = 0.0039) on chromosome 1 between marker D1S1592 and D1S1598. Our results suggest that reordering fine-mapping markers in candidate regions when the genetic map is uncertain can be a critical step when considering a dense map

Structural equation model-based genome scan for the metabolic syndrome

BACKGROUND: The metabolic syndrome is characterized by the clustering of several traits, including obesity, hypertension, decreased levels of HDL cholesterol, and increased levels of glucose and triglycerides. Because these traits cluster, there are likely common genetic factors involved. RESULTS: We used a multivariate structural equation model (SEM) approach to scan the genome for loci involved in the metabolic syndrome. We found moderate evidence for linkage on chromosomes 2, 3, 11, 13, and 15, and these loci appear to have different relative effects on the component traits of the metabolic syndrome. CONCLUSION: Our results suggest that the metabolic syndrome components, diabetes, obesity, and hypertension, are under the pleiotropic control of several loci

Using linkage analysis of large pedigrees to guide association analyses

To date, genome-wide association studies have yielded discoveries of common variants that partly explain familial aggregation of diseases and traits. Researchers are now turning their attention to less common variants because the price of sequencing has dropped drastically. However, because sequencing of the whole genome in large samples is costly, great care must be taken to prioritize which samples and which genomic regions are selected for sequencing. We are interested in identifying genomic regions for deep sequencing using large multiplex families collected as part of earlier linkage studies. We incorporate linkage analysis into our search for Q1-associated alleles. Overall, we found that power was low for both whole-exome and linkage-guided sequencing analysis. By restricting sequencing to regions with high LOD peaks, we found fewer associated single-nucleotide polymorphisms than by using whole-exome sequencing. However, incorporating linkage analysis enabled us to detect more than half of the associated susceptibility loci (52%) that would have been identified by whole-exome sequencing while examining only 2.5% of the exome. This result suggests that incorporating linkage results from large multiplex families might greatly increase the efficiency of sequencing to detect trait-associated alleles in complex disease

Using community-based geographical information system (GIS) to recruit older Asian Americans in an Alzheimers disease study.

OBJECTIVE: This study aims to show the usefulness of incorporating a community-based geographical information system (GIS) in recruiting research participants for the Asian Cohort for Alzheimers Disease (ACAD) study for using the subgroup of Korean American (KA) older adults. The ACAD study is the first large study in the USA and Canada focusing on the recruitment of Chinese, Korean and Vietnamese older adults to address the issues of under-representation of Asian Americans in clinical research. METHODS: To promote clinical research participation of racial/ethnic minority older adults with and without dementia, we used GIS by collaborating with community members to delineate boundaries for geographical clusters and enclaves of church and senior networks, and KA serving ethnic clinics. In addition, we used socioeconomic data identified as recruitment factors unique to KA older adults which was analysed for developing recruitment strategies. RESULTS: GIS maps show a visualisation of the heterogeneity of the sociodemographic characteristics and the resources of faith-based organisations and KA serving local clinics. We addressed these factors that disproportionately affect participation in clinical research and successfully recruited the intended participants (N=60) in the proposed period. DISCUSSION: Using GIS maps to locate KA provided innovative inroads to successful research outreach efforts for a pilot study that may be expanded to other underserved populations across the USA in the future. We will use this tool subsequently on a large-scale clinical genetic epidemiology study. POLICY IMPLICATION: This approach responds to the call from the National Institute on Aging to develop strategies to improve the health status of older adults in diverse populations. Our study will offer a practical guidance to health researchers and policymakers in identifying understudied and hard-to-reach specific Asian American populations for clinical studies or initiatives. This would further contribute in reducing the health and research disparity gaps among older minority populations

Genome-wide analyses demonstrate novel loci that predispose to drusen formation

PURPOSE. To test whether genes for drusen formation are independent of age-related macular degeneration (AMD) pathogenesis. METHODS. A genome-wide model-free linkage analysis was performed, using two semiquantitative drusen traits, size and type, on two sets of data: (1) 325 individuals (225 sib pairs) from the Beaver Dam Eye Study (BDES), and (2) 297 individuals (346 sib pairs) from the Family Age Related Maculopathy Study (FARMS). Apolipoprotein E (APOE) genotypes were used as a covariate in a multipoint sibpair analysis. RESULTS. The authors found evidence of linkage on 19q13.31 (D19S245), with size of drusen in both the BDES (P ϭ 0.0287) and the FARMS (P ϭ 0.0013; P ϭ 0.0005, combined). In the BDES, type showed linkage evidence on 3p24.3 (D3S1768; P ϭ 0.0189) and 3q25.1 (D3S2404; P ϭ 0.0141); the linkage on 3p24.3 was also found with size (D3S1768; P ϭ 0.0264). In the FARMS, size showed evidence of linkage at 5q33.3 (D5S820; P ϭ 0.0021), 14q32.33 (D14S1007; P ϭ 0.0013), and 16p13.13 (D16S2616; P ϭ 0.0015) and type at 21q21.2 (D21S2052; P ϭ 0.0070). For size in the FARMS, there was a small increase in P-value at marker D19S245 from 0.0044 to 0.0111, and from 0.0044 to 0.0064, when the 4-carrier and the 3-carrier genotype were the covariates, respectively. CONCLUSIONS. The results show that APOE effects may be mediated early in the progression of ARM to AMD and thus may not be detected by standard genome scans for more severe disease. (Invest Ophthalmol Vis Sci. 2005;46:3081-3088

PLXNA4 is associated with Alzheimer disease and modulates tau phosphorylation

OBJECTIVE: Much of the genetic basis for Alzheimer disease (AD) is unexplained. We sought to identify novel AD loci using a unique family-based approach that can detect robust associations with infrequent variants (minor allele frequency < 0.10). METHODS: We conducted a genome-wide association study in the Framingham Heart Study (discovery) and NIA-LOAD (National Institute on Aging-Late-Onset Alzheimer Disease) Study (replication) family-based cohorts using an approach that accounts for family structure and calculates a risk score for AD as the outcome. Links between the most promising gene candidate and AD pathogenesis were explored in silico as well as experimentally in cell-based models and in human brain. RESULTS: Genome-wide significant association was identified with a PLXNA4 single nucleotide polymorphism (rs277470) located in a region encoding the semaphorin-3A (SEMA3A) binding domain (meta-analysis p value [meta-P] = 4.1 × 10(-8) ). A test for association with the entire region was also significant (meta-P = 3.2 × 10(-4) ). Transfection of SH-SY5Y cells or primary rat neurons with full-length PLXNA4 (TS1) increased tau phosphorylation with stimulated by SEMA3A. The opposite effect was observed when cells were transfected with shorter isoforms (TS2 and TS3). However, transfection of any isoform into HEK293 cells stably expressing amyloid β (Aβ) precursor protein (APP) did not result in differential effects on APP processing or Aβ production. Late stage AD cases (n = 9) compared to controls (n = 5) had 1.9-fold increased expression of TS1 in cortical brain tissue (p = 1.6 × 10(-4) ). Expression of TS1 was significantly correlated with the Clinical Dementia Rating score (ρ = 0.75, p = 2.2 × 10(-4) ), plaque density (ρ = 0.56, p = 0.01), and Braak stage (ρ = 0.54, p = 0.02). INTERPRETATION: Our results indicate that PLXNA4 has a role in AD pathogenesis through isoform-specific effects on tau phosphorylation

Genome-wide pleiotropy analysis of neuropathological traits related to Alzheimer’s disease

Background Simultaneous consideration of two neuropathological traits related to Alzheimer’s disease (AD) has not been attempted in a genome-wide association study. Methods We conducted genome-wide pleiotropy analyses using association summary statistics from the Beecham et al. study (PLoS Genet 10:e1004606, 2014) for AD-related neuropathological traits, including neuritic plaque (NP), neurofibrillary tangle (NFT), and cerebral amyloid angiopathy (CAA). Significant findings were further examined by expression quantitative trait locus and differentially expressed gene analyses in AD vs. control brains using gene expression data. Results Genome-wide significant pleiotropic associations were observed for the joint model of NP and NFT (NP + NFT) with the single-nucleotide polymorphism (SNP) rs34487851 upstream of C2orf40 (alias ECRG4, P = 2.4 × 10−8) and for the joint model of NFT and CAA (NFT + CAA) with the HDAC9 SNP rs79524815 (P = 1.1 × 10−8). Gene-based testing revealed study-wide significant associations (P ≤ 2.0 × 10−6) for the NFT + CAA outcome with adjacent genes TRAPPC12, TRAPPC12-AS1, and ADI1. Risk alleles of proxy SNPs for rs79524815 were associated with significantly lower expression of HDAC9 in the brain (P = 3.0 × 10−3), and HDAC9 was significantly downregulated in subjects with AD compared with control subjects in the prefrontal (P = 7.9 × 10−3) and visual (P = 5.6 × 10−4) cortices. Conclusions Our findings suggest that pleiotropy analysis is a useful approach to identifying novel genetic associations with complex diseases and their endophenotypes. Functional studies are needed to determine whether ECRG4 or HDAC9 is plausible as a therapeutic target