Non-skeletal activities of vitamin d: From physiology to brain pathology

Vitamin D is a secosteroid hormone regulating the expression of almost 900 genes, and it is involved in the regulation of calcium and phosphate metabolism, immune response, and brain development. Low blood vitamin D levels have been reported in patients affected by various diseases. Despite a large amount of literature data, there is uncertainty surrounding the role of vitamin D as a serum biomarker in Alzheimer’s disease (AD) and Parkinson’s disease (PD). Indeed, the lack of internationally recognized 25(OH)D3 reference measurement procedures and standard materials in the past led to unstandardized serum total 25(OH)D3 results among research and clinical care laboratories. Thus, most of the literature studies reported unstandardized data, which are of little use and make it difficult to draw conclusions of the role of vitamin D in AD and PD. This review summarizes the extra-skeletal actions of vitamin D, focusing its role in immunomodulation and brain function, and reports the issue of lacking standardized literature data concerning the usefulness of vitamin D as a biomarker in AD and PD

A neurogenetic model for the study of schizophrenia spectrum disorders: The International 22q11.2 Deletion Syndrome Brain Behavior Consortium

Rare copy number variants contribute significantly to the risk for schizophrenia, with the 22q11.2 locus consistently implicated. Individuals with the 22q11.2 deletion syndrome (22q11DS) have an estimated 25-fold increased risk for schizophrenia spectrum disorders, compared to individuals in the general population. The International 22q11DS Brain Behavior Consortium is examining this highly informative neurogenetic syndrome phenotypically and genomically. Here we detail the procedures of the effort to characterize the neuropsychiatric and neurobehavioral phenotypes associated with 22q11DS, focusing on schizophrenia and subthreshold expression of psychosis. The genomic approach includes a combination of whole genome sequencing and genome-wide microarray technologies, allowing the investigation of all possible DNA variation and gene pathways influencing the schizophrenia-relevant phenotypic expression. A phenotypically rich data set provides a psychiatrically well-characterized sample of unprecedented size (n=1,616) that informs the neurobehavioral developmental course of 22q11DS. This combined set of phenotypic and genomic data will enable hypothesis testing to elucidate the mechanisms underlying the pathogenesis of schizophrenia spectrum disorders

Copy Number Variants in Extended Autism Spectrum Disorder Families Reveal Candidates Potentially Involved in Autism Risk

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

Genomic Contributors to Individual Differences in Reward-Related Neural Activity

Aberrant reward-related behavior, including impulsive and risk-taking behaviors, is a common feature of externalizing psychopathology (e.g., attention deficit hyperactivity disorder, antisocial personality disorder, and substance-use disorders). Through imaging studies, these behaviors have been linked to dysregulated reactivity within a diffuse reward-related corticostriatal neural network, including the striatum, frontal regions (namely orbital, ventromedial, and dorsolateral cortices), the insula, and the hippocampus. Because variability in risk-taking behavior and related psychopathology is moderately-to-largely heritable (i.e., with estimates ranging from 40 – 80%), a genetically-informed approach is well-positioned to provide valuable insight into the etiology of reward-related neural and behavioral phenotypes that characterize externalizing psychopathology. Using summary statistics from a recent genome-wide association study (GWAS) of risk tolerance among 939,908 individuals, we generated polygenic risk scores (PRS) for a European-ancestry subsample (usable data ranging from n=457 to n=518; see Table 2) of the Duke Neurogenetics Study (DNS; a large community sample) and examined associations between genomic liability and risk-taking phenotypes (i.e., self-reported impulsivity and alcohol use, and behavioral delay discounting), as well as BOLD activation of the ventral striatum. Contrary to our hypotheses, GWAS-based PRS were not consistently significantly associated with risk-related behavior or with activation of the ventral striatum. In order to increase biological informativeness, we also used PrediXcan analyses to identify genes with differential expression based on the risk-related genomic liability; however, PRS of these differentially-expressed variants were also not significantly associated with risk-related behavioral or neural-activation phenotypes in the DNS. Though these null findings may reflect a true lack of association between risk-related genetic liability and behavior/neural externalizing phenotypes, we discuss possible alternative explanations regarding imprecise phenotyping in the discovery GWAS, inadequate statistical power, and questionable reliability of task-based fMRI measurements

Integrating fMRI and SNP data for biomarker identification for schizophrenia with a sparse representation based variable selection method

BACKGROUND: In recent years, both single-nucleotide polymorphism (SNP) array and functional magnetic resonance imaging (fMRI) have been widely used for the study of schizophrenia (SCZ). In addition, a few studies have been reported integrating both SNPs data and fMRI data for comprehensive analysis. METHODS: In this study, a novel sparse representation based variable selection (SRVS) method has been proposed and tested on a simulation data set to demonstrate its multi-resolution properties. Then the SRVS method was applied to an integrative analysis of two different SCZ data sets, a Single-nucleotide polymorphism (SNP) data set and a functional resonance imaging (fMRI) data set, including 92 cases and 116 controls. Biomarkers for the disease were identified and validated with a multivariate classification approach followed by a leave one out (LOO) cross-validation. Then we compared the results with that of a previously reported sparse representation based feature selection method. RESULTS: Results showed that biomarkers from our proposed SRVS method gave significantly higher classification accuracy in discriminating SCZ patients from healthy controls than that of the previous reported sparse representation method. Furthermore, using biomarkers from both data sets led to better classification accuracy than using single type of biomarkers, which suggests the advantage of integrative analysis of different types of data. CONCLUSIONS: The proposed SRVS algorithm is effective in identifying significant biomarkers for complicated disease as SCZ. Integrating different types of data (e.g. SNP and fMRI data) may identify complementary biomarkers benefitting the diagnosis accuracy of the disease

A large population-based investigation into the genetics of susceptibility to gastrointestinal infections and the link between gastrointestinal infections and mental illness.

Gastrointestinal infections can be life threatening, but not much is known about the host's genetic contribution to susceptibility to gastrointestinal infections or the latter's association with psychiatric disorders. We utilized iPSYCH, a genotyped population-based sample of individuals born between 1981 and 2005 comprising 65,534 unrelated Danish individuals (45,889 diagnosed with mental disorders and 19,645 controls from a random population sample) in which all individuals were linked utilizing nationwide population-based registers to estimate the genetic contribution to susceptibility to gastrointestinal infections, identify genetic variants associated with gastrointestinal infections, and examine the link between gastrointestinal infections and psychiatric and neurodevelopmental disorders. The SNP heritability of susceptibility to gastrointestinal infections ranged from 3.7% to 6.4% on the liability scale. Significant correlations were found between gastrointestinal infections and the combined group of mental disorders (OR = 2.09; 95% CI: 1.82-2.4, P = 1.87 × 10-25). Correlations with autism spectrum disorder, attention deficit hyperactivity disorder, and depression were also significant. We identified a genome-wide significant locus associated with susceptibility to gastrointestinal infections (OR = 1.13; 95% CI: 1.08-1.18, P = 2.9 × 10-8), where the top SNP was an eQTL for the ABO gene. The risk allele was associated with reduced ABO expression, providing, for the first time, genetic evidence to support previous studies linking the O blood group to gastrointestinal infections. This study also highlights the importance of integrative work in genetics, psychiatry, infection, and epidemiology on the road to translational medicine

Evolutionary conservation in genes underlying human psychiatric disorders

Many psychiatric diseases observed in humans have tenuous or absent analogs in other species. Most notable among these are schizophrenia and autism. One hypothesis has posited that these diseases have arisen as a consequence of human brain evolution, for example, that the same processes that led to advances in cognition, language, and executive function also resulted in novel diseases in humans when dysfunctional. Here, the molecular evolution of the protein-coding regions of genes associated with these and other psychiatric disorders are compared among species. Genes associated with psychiatric disorders are drawn from the literature and orthologous sequences are collected from eleven primate species (human, chimpanzee, bonobo, gorilla, orangutan, gibbon, macaque, baboon, marmoset, squirrel monkey, and galago) and 34 non-primate mammalian species. Evolutionary parameters, including dN/dS, are calculated for each gene and compared between disease classes and among species, focusing on humans and primates compared to other mammals, and on large-brained taxa (cetaceans, rhinoceros, walrus, bear, and elephant) compared to their small-brained sister species. Evidence of differential selection in humans to the exclusion of non-human primates was absent, however elevated dN/dS was detected in catarrhines as a whole, as well as in cetaceans, possibly as part of a more general trend. Although this may suggest that protein changes associated with schizophrenia and autism are not a cost of the higher brain function found in humans, it may also point to insufficiencies in the study of these diseases including incomplete or inaccurate gene association lists and/or a greater role of regulatory changes or copy number variation. Through this work a better understanding of the molecular evolution of the human brain, the pathophysiology of disease, and the genetic basis of human psychiatric disease is gained

Stem-Like Adaptive Aneuploidy and Cancer Quasispecies

We analyze and reinterpret experimental evidence from the literature to argue for an ability of tumor cells to self-regulate their aneuploidy rate. We conjecture that this ability is mediated by a diversification factor that exploits molecular mechanisms common to embryo stem cells and, to a lesser extent, adult stem cells, that is eventually reactivated in tumor cells. Moreover, we propose a direct use of the quasispecies model to cancer cells based on their significant genomic instability (i.e. aneuploidy rate), by defining master sequences lengths as the sum of all copy numbers of physically distinct whole and fragmented chromosomes. We compute an approximate error threshold such that any aneuploidy rate larger than the threshold would lead to a loss of fitness of a tumor population, and we confirm that highly aneuploid cancer populations already function with aneuploidy rates close to the estimated threshold

Treating Bipolar Disorder and Schizophrenia with Biomedical Protocol

Bipolar Disorder and schizophrenia afflict approximately 2% of the human population, more than 12,400,000 people. When family members, co-workers, and care-givers are factored in, more than 10% of the population is directly impacted by these medical conditions. Finding a way to reduce the severity of the symptoms or cure these diseases would positively impact a large number of people. This paper defines and differentiates between these two similar-but-different maladies, and explores both the traditional courses of treatment as well as the most current research with potential to help combat these diseases – especially genetic mapping with the use of neuroimaging. Because genetic mapping has been successfully used to treat cancers, applying this technique to neurological disorders is the next logical step to take