A quantitative trait rare variant nonparametric linkage method with application to age-at-onset of Alzheimer's disease

The National Institute on Aging Late-Onset Alzheimer's Disease Family Based Study: A resource for genetic discovery

INTRODUCTION

The National Institute on Aging Late-Onset Alzheimer's Disease Family Based Study (NIA-LOAD FBS) was established to study the genetic etiology of Alzheimer's disease (AD).

METHODS

Recruitment focused on families with two living affected siblings and a third first-degree relative similar in age with or without dementia. Uniform assessments were completed, DNA was obtained, as was neuropathology, when possible. Apolipoprotein E (APOE) genotypes, genome-wide single nucleotide polymorphism (SNP) arrays, and sequencing was completed in most families.

RESULTS

APOE genotype modified the age-at-onset in many large families. Novel variants and known variants associated with early- and late-onset AD and frontotemporal dementia were identified supporting an international effort to solve AD genetics.

DISCUSSION

The NIA-LOAD FBS is the largest collection of familial AD worldwide, and data or samples have been included in 123 publications addressing the genetic etiology of AD. Genetic heterogeneity and variability in the age-at-onset provides opportunities to investigate the complexity of familial AD.

Novel Alzheimer risk factor IQ motif containing protein K is abundantly expressed in the brain and is markedly increased in patients with Alzheimer’s disease

Alzheimer’s disease (AD) is complex and highly heterogeneous. Less than 10% of AD cases are early-onset (EOAD) caused by autosomal dominantly inherited mutations in amyloid precursor protein (APP), presenilin 1 (PS1), or presenilin 2 (PS2), each of which can increase Aβ generation and, thus, amyloid plaques. The remaining 90% of cases of AD are late-onset (LOAD) or sporadic. Intense research efforts have led to identification of many genes that increase the risk of AD. An IQ motif containing protein K (IQCK) was recently identified by several investigators as an Alzheimer’s disease risk gene. However, how IQCK increases AD risk is completely unknown. Since IQCK is a novel gene, there is limited information on its physiological characterization. To understand its role in AD, it is first important to determine its subcellular localization, whether and where it is expressed in the brain, and what type of brain cells express the IQCK protein. Therefore, in this study, we show by immunocytochemical (ICC) staining that IQCK is expressed in both the nucleus and the cytoplasm of SH-SY5Y neuroblastoma cells as well as HeLa cells but not in either HMC3 microglial or CHO cells. By immunohistochemistry (IHC), we also show that IQCK is expressed in both mouse and human neurons, including neuronal processes in vivo in the mouse brain. IHC data also show that the IQCK protein is widely expressed throughout the mouse brain, although regional differences were noted. IQCK expression was highest in the brainstem (BS), followed by the cerebellum (CB) and the cortex (CX), and it was lowest in the hippocampus (HP). This finding was consistent with data from an immunoblot analysis of brain tissue homogenates. Interestingly, we found IQCK expression in neurons, astrocytes, and oligodendrocytes using cell-specific antibodies, but IQCK was not detected in microglial cells, consistent with negative in vitro results in HMC3 cells. Most importantly, we found that actin-normalized IQCK protein levels were increased by 2 folds in AD brains relative to normal control (NC) brains. Furthermore, the IQCK protein was found in amyloid plaques, suggesting that IQCK may play a pathogenic role in either Aβ generation or amyloid plaque deposition in AD.

Novel Approach Combining Transcriptional and Evolutionary Signatures to Identify New Multiciliation Genes

Multiciliogenesis is a complex process that allows the generation of hundreds of motile cilia on the surface of specialized cells, to create fluid flow across epithelial surfaces. Dysfunction of human multiciliated cells is associated with diseases of the brain, airway and reproductive tracts. Despite recent efforts to characterize the transcriptional events responsible for the differentiation of multiciliated cells, a lot of actors remain to be identified. In this work, we capitalize on the ever-growing quantity of high-throughput data to search for new candidate genes involved in multiciliation. After performing a large-scale screening using 10 transcriptomics datasets dedicated to multiciliation, we established a specific evolutionary signature involving Otomorpha fish to use as a criterion to select the most likely targets. Combining both approaches highlighted a list of 114 potential multiciliated candidates. We characterized these genes first by generating protein interaction networks, which showed various clusters of ciliated and multiciliated genes, and then by computing phylogenetic profiles. In the end, we selected 11 poorly characterized genes that seem like particularly promising multiciliated candidates. By combining functional and comparative genomics methods, we developed a novel type of approach to study biological processes and identify new promising candidates linked to that process.