Genetic basis of human circadian rhythm disorders.

Circadian rhythm disorders constitute a group of phenotypes that usually present as altered sleep-wake schedules. Until a human genetics approach was applied to investigate these traits, the genetic components regulating human circadian rhythm and sleep behaviors remained mysterious. Steady advances in the last decade have dramatically improved our understanding of the genes involved in circadian rhythmicity and sleep regulation. Finding these genes presents new opportunities to use a wide range of approaches, including in vitro molecular studies and in vivo animal modeling, to elevate our understanding of how sleep and circadian rhythms are regulated and maintained. Ultimately, this knowledge will reveal how circadian and sleep disruption contribute to various ailments and shed light on how best to maintain and recover good health

Casein kinase iδ mutations in familial migraine and advanced sleep phase.

Migraine is a common disabling disorder with a significant genetic component, characterized by severe headache and often accompanied by nausea, vomiting, and light sensitivity. We identified two families, each with a distinct missense mutation in the gene encoding casein kinase Iδ (CKIδ), in which the mutation cosegregated with both the presence of migraine and advanced sleep phase. The resulting alterations (T44A and H46R) occurred in the conserved catalytic domain of CKIδ, where they caused reduced enzyme activity. Mice engineered to carry the CKIδ-T44A allele were more sensitive to pain after treatment with the migraine trigger nitroglycerin. CKIδ-T44A mice also exhibited a reduced threshold for cortical spreading depression (believed to be the physiological analog of migraine aura) and greater arterial dilation during cortical spreading depression. Astrocytes from CKIδ-T44A mice showed increased spontaneous and evoked calcium signaling. These genetic, cellular, physiological, and behavioral analyses suggest that decreases in CKIδ activity can contribute to the pathogenesis of migraine

Bone mineral as a drug-seeking moiety and a waste dump

Bone is a dynamic tissue with a quarter of the trabecular and a fifth of the cortical bone being replaced continuously each year in a complex process that continues throughout an individual’s lifetime. Bone has an important role in homeostasis of minerals with non-stoichiometric hydroxyapatite bone mineral forming the inorganic phase of bone. Due to its crystal structure and chemistry, hydroxyapatite (HA) and related apatites have a remarkable ability to bind molecules. This review article describes the accretion of trace elements in bone mineral giving a historical perspective. Implanted HA particles of synthetic origin have proved to be an efficient recruiting moiety for systemically circulating drugs which can locally biomodulate the material and lead to a therapeutic effect. Bone mineral and apatite however also act as a waste dump for trace elements and drugs, which significantly affects the environment and human health

COL25A1 triggers and promotes Alzheimer’s disease-like pathology in vivo

Collagen XXV alpha 1 (COL25A1) is a collagenous type II transmembrane protein purified from senile plaques of Alzheimer’s disease (AD) brains. COL25A1 alleles have been associated with increased risk for AD in a Swedish population. COL25A1 is specifically expressed in neurons and binds to aggregated Aβ in vitro. However, its contribution to the pathogenesis of AD and in vivo function are unknown. Here, we report that over-expression of COL25A1 in transgenic mice increases p35/p25 and β-site APP-cleaving enzyme 1 (BACE1) levels, facilitates intracellular aggregation and extracellular matrix deposits of Aβ, and causes synaptophysin loss and astrocyte activation. COL25A1 mice displayed reduced anxiety-like behavior in elevated plus maze and open field tests and significantly slower swimming speed in Morris water maze. In stable cell lines, motifs in noncollagenous domains of COL25A1 were important for the induction of BACE1 expression. These findings demonstrate that COL25A1 leads to AD-like pathology in vivo. Modulation of COL25A1 function may represent an alternative therapeutic intervention for AD

Guidelines for Genome-Scale Analysis of Biological Rhythms

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding “big data” that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them

Alternating hemiplegia of childhood: Retrospective genetic study and genotype-phenotype correlations in 187 subjects from the US AHCF registry

Mutations in ATP1A3 cause Alternating Hemiplegia of Childhood (AHC) by disrupting function of the neuronal Na+/K+ ATPase. Published studies to date indicate 2 recurrent mutations, D801N and E815K, and a more severe phenotype in the E815K cohort. We performed mutation analysis and retrospective genotype-phenotype correlations in all eligible patients with AHC enrolled in the US AHC Foundation registry from 1997-2012. Clinical data were abstracted from standardized caregivers' questionnaires and medical records and confirmed by expert clinicians. We identified ATP1A3 mutations by Sanger and whole genome sequencing, and compared phenotypes within and between 4 groups of subjects, those with D801N, E815K, other ATP1A3 or no ATP1A3 mutations. We identified heterozygous ATP1A3 mutations in 154 of 187 (82%) AHC patients. Of 34 unique mutations, 31 (91%) are missense, and 16 (47%) had not been previously reported. Concordant with prior studies, more than 2/3 of all mutations are clustered in exons 17 and 18. Of 143 simplex occurrences, 58 had D801N (40%), 38 had E815K (26%) and 11 had G937R (8%) mutations. Patients with an E815K mutation demonstrate an earlier age of onset, more severe motor impairment and a higher prevalence of status epilepticus. This study further expands the number and spectrum of ATP1A3 mutations associated with AHC and confirms a more deleterious effect of the E815K mutation on selected neurologic outcomes. However, the complexity of the disorder and the extensive phenotypic variability among subgroups merits caution and emphasizes the need for further studies

Guidelines for Genome-Scale Analysis of Biological Rhythms

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding ‘big data’ that is conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them