Transcriptome analysis of cortical tissue reveals shared sets of downregulated genes in autism and schizophrenia.

Autism (AUT), schizophrenia (SCZ) and bipolar disorder (BPD) are three highly heritable neuropsychiatric conditions. Clinical similarities and genetic overlap between the three disorders have been reported; however, the causes and the downstream effects of this overlap remain elusive. By analyzing transcriptomic RNA-sequencing data generated from post-mortem cortical brain tissues from AUT, SCZ, BPD and control subjects, we have begun to characterize the extent of gene expression overlap between these disorders. We report that the AUT and SCZ transcriptomes are significantly correlated (P<0.001), whereas the other two cross-disorder comparisons (AUT-BPD and SCZ-BPD) are not. Among AUT and SCZ, we find that the genes differentially expressed across disorders are involved in neurotransmission and synapse regulation. Despite the lack of global transcriptomic overlap across all three disorders, we highlight two genes, IQSEC3 and COPS7A, which are significantly downregulated compared with controls across all three disorders, suggesting either shared etiology or compensatory changes across these neuropsychiatric conditions. Finally, we tested for enrichment of genes differentially expressed across disorders in genetic association signals in AUT, SCZ or BPD, reporting lack of signal in any of the previously published genome-wide association study (GWAS). Together, these studies highlight the importance of examining gene expression from the primary tissue involved in neuropsychiatric conditions-the cortical brain. We identify a shared role for altered neurotransmission and synapse regulation in AUT and SCZ, in addition to two genes that may more generally contribute to neurodevelopmental and neuropsychiatric conditions

The functional "KL-VS" variant of KLOTHO is not associated with type 2 diabetes in 5028 UK Caucasians

BACKGROUND: Klotho has an important role in insulin signalling and the development of ageing-like phenotypes in mice. The common functional "KL-VS" variant in the KLOTHO (KL) gene is associated with longevity in humans but its role in type 2 diabetes is not known. We performed a large case-control and family-based study to test the hypothesis that KL-VS is associated with type 2 diabetes in a UK Caucasian population. METHODS: We genotyped 1793 cases, 1619 controls and 1616 subjects from 509 families for the single nucleotide polymorphism (SNP) F352V (rs9536314) that defines the KL-VS variant. Allele and genotype frequencies were compared between cases and controls. Family-based analysis was used to test for over- or under-transmission of V352 to affected offspring. RESULTS: Despite good power to detect odds ratios of 1.2, there were no significant associations between alleles or genotypes and type 2 diabetes (V352 allele: odds ratio = 0.96 (0.84–1.09)). Additional analysis of quantitative trait data in 1177 healthy control subjects showed no association of the variant with fasting insulin, glucose, triglycerides, HDL- or LDL-cholesterol (all P > 0.05). However, the HDL-cholesterol levels observed across the genotype groups showed a similar, but non-significant, pattern to previously reported data. CONCLUSION: This is the first large-scale study to examine the association between common functional variation in KL and type 2 diabetes risk. We have found no evidence that the functional KL-VS variant is a risk factor for type 2 diabetes in a large UK Caucasian case-control and family-based study

A genome-wide linkage and association scan reveals novel loci for autism

Although autism is a highly heritable neurodevelopmental disorder, attempts to identify specific susceptibility genes have thus far met with limited success. Genome-wide association studies using half a million or more markers, particularly those with very large sample sizes achieved through meta-analysis, have shown great success in mapping genes for other complex genetic traits. Consequently, we initiated a linkage and association mapping study using half a million genome-wide single nucleotide polymorphisms (SNPs) in a common set of 1,031 multiplex autism families (1,553 affected offspring). We identified regions of suggestive and significant linkage on chromosomes 6q27 and 20p13, respectively. Initial analysis did not yield genome-wide significant associations; however, genotyping of top hits in additional families revealed an SNP on chromosome 5p15 (between SEMA5A and TAS2R1) that was significantly associated with autism (P = 2 x 10(-7)). We also demonstrated that expression of SEMA5A is reduced in brains from autistic patients, further implicating SEMA5A as an autism susceptibility gene. The linkage regions reported here provide targets for rare variation screening whereas the discovery of a single novel association demonstrates the action of common variants

Consequences of increased longevity for wealth, fertility, and population growth

We present, solve and numerically simulate a simple model that describes the consequences of increased longevity on fertility rates, population growth and the distribution of wealth in developed societies. We look at the consequences of the repeated use of life extension techniques and show that they represent a novel commodity whose introduction will profoundly influence key aspects of economy and society in general. In particular, we uncover two phases within our simplified model, labeled as 'mortal' and 'immortal'. Within the life extension scenario it is possible to have sustainable economic growth in a population of stable size, as a result of dynamical equilibrium between the two phases.Comment: 13 pages, 5 figures, uses elsart.cl

Klotho Lacks a Vitamin D Independent Physiological Role in Glucose Homeostasis, Bone Turnover, and Steady-State PTH Secretion In Vivo

Apart from its function as co-receptor for fibroblast growth factor-23 (FGF23), Klotho is thought to regulate insulin signaling, intracellular oxidative stress, and parathyroid hormone (PTH) secretion in an FGF23 independent fashion. Here, we crossed Klotho deficient (Kl−/−) mice with vitamin D receptor (VDR) mutant mice to examine further vitamin D independent functions of Klotho. All mice were fed a rescue diet enriched with calcium, phosphorus, and lactose to prevent hyperparathyroidism in VDR mutants, and were killed at 4 weeks of age after double fluorochrome labeling. Kl−/− mice displayed hypercalcemia, hyperphosphatemia, dwarfism, organ atrophy, azotemia, pulmonary emphysema, and osteomalacia. In addition, glucose and insulin tolerance tests revealed hypoglycemia and profoundly increased peripheral insulin sensitivity in Kl−/− mice. Compound mutants were normocalcemic and normophosphatemic, did not show premature aging or organ atrophy, and were phenocopies of VDR mutant mice in terms of body weight, bone mineral density, bone metabolism, serum calcium, serum phosphate, serum PTH, gene expression in parathyroid glands, as well as urinary calcium and phosphate excretion. Furthermore, ablation of vitamin D signaling in double mutants completely normalized glucose and insulin tolerance, indicating that Klotho has no vitamin D independent effects on insulin signaling. Histomorphometry of pancreas islets showed similar beta cell volume per body weight in all groups of animals. In conclusion, our findings cast doubt on a physiologically relevant vitamin D and Fgf23 independent function of Klotho in the regulation of glucose metabolism, bone turnover, and steady-state PTH secretion in vivo

Aging syndrome genes and premature coronary artery disease

BACKGROUND: Vascular disease is a feature of aging, and coronary vascular events are a major source of morbidity and mortality in rare premature aging syndromes. One such syndrome is caused by mutations in the lamin A/C (LMNA) gene, which also has been implicated in familial insulin resistance. A second gene related to premature aging in man and in murine models is the KLOTHO gene, a hypomorphic variant of which (KL-VS) is significantly more common in the first-degree relatives of patients with premature coronary artery disease (CAD). We evaluated whether common variants at the LMNA or KLOTHO genes are associated with rigorously defined premature CAD. METHODS: We identified 295 patients presenting with premature acute coronary syndromes confirmed by angiography. A control group of 145 patients with no evidence of CAD was recruited from outpatient referral clinics. Comprehensive haplotyping of the entire LMNA gene, including the promoter and untranslated regions, was performed using a combination of TaqMan(® )probes and direct sequencing of 14 haplotype-tagging single nucleotide polymorphisms (SNPs). The KL-VS variant of the KLOTHO gene was typed using restriction digest of a PCR amplicon. RESULTS: Two SNPs that were not in Hardy Weinberg equilibrium were excluded from analysis. We observed no significant differences in allele, genotype or haplotype frequencies at the LMNA or KLOTHO loci between the two groups. In addition, there was no evidence of excess homozygosity at the LMNA locus. CONCLUSION: Our data do not support the hypothesis that premature CAD is associated with common variants in the progeroid syndrome genes LMNA and KLOTHO

Multiple Independent Genetic Factors at NOS1AP Modulate the QT Interval in a Multi-Ethnic Population

Extremes of electrocardiographic QT interval are associated with increased risk for sudden cardiac death (SCD); thus, identification and characterization of genetic variants that modulate QT interval may elucidate the underlying etiology of SCD. Previous studies have revealed an association between a common genetic variant in NOS1AP and QT interval in populations of European ancestry, but this finding has not been extended to other ethnic populations. We sought to characterize the effects of NOS1AP genetic variants on QT interval in the multi-ethnic population-based Dallas Heart Study (DHS, n = 3,072). The SNP most strongly associated with QT interval in previous samples of European ancestry, rs16847548, was the most strongly associated in White (P = 0.005) and Black (P = 3.6×10−5) participants, with the same direction of effect in Hispanics (P = 0.17), and further showed a significant SNP × sex-interaction (P = 0.03). A second SNP, rs16856785, uncorrelated with rs16847548, was also associated with QT interval in Blacks (P = 0.01), with qualitatively similar results in Whites and Hispanics. In a previously genotyped cohort of 14,107 White individuals drawn from the combined Atherosclerotic Risk in Communities (ARIC) and Cardiovascular Health Study (CHS) cohorts, we validated both the second locus at rs16856785 (P = 7.63×10−8), as well as the sex-interaction with rs16847548 (P = 8.68×10−6). These data extend the association of genetic variants in NOS1AP with QT interval to a Black population, with similar trends, though not statistically significant at P<0.05, in Hispanics. In addition, we identify a strong sex-interaction and the presence of a second independent site within NOS1AP associated with the QT interval. These results highlight the consistent and complex role of NOS1AP genetic variants in modulating QT interval

A fast algorithm for genome-wide haplotype pattern mining

<p>Abstract</p> <p>Background</p> <p>Identifying the genetic components of common diseases has long been an important area of research. Recently, genotyping technology has reached the level where it is cost effective to genotype single nucleotide polymorphism (SNP) markers covering the entire genome, in thousands of individuals, and analyse such data for markers associated with a diseases. The statistical power to detect association, however, is limited when markers are analysed one at a time. This can be alleviated by considering multiple markers simultaneously. The <it>Haplotype Pattern Mining </it>(HPM) method is a machine learning approach to do exactly this.</p> <p>Results</p> <p>We present a new, faster algorithm for the HPM method. The new approach use patterns of haplotype diversity in the genome: locally in the genome, the number of observed haplotypes is much smaller than the total number of possible haplotypes. We show that the new approach speeds up the HPM method with a factor of 2 on a genome-wide dataset with 5009 individuals typed in 491208 markers using default parameters and more if the pattern length is increased.</p> <p>Conclusion</p> <p>The new algorithm speeds up the HPM method and we show that it is feasible to apply HPM to whole genome association mapping with thousands of individuals and hundreds of thousands of markers.</p

Indirect two-sided relative ranking: a robust similarity measure for gene expression data

<p>Abstract</p> <p>Background</p> <p>There is a large amount of gene expression data that exists in the public domain. This data has been generated under a variety of experimental conditions. Unfortunately, these experimental variations have generally prevented researchers from accurately comparing and combining this wealth of data, which still hides many novel insights.</p> <p>Results</p> <p>In this paper we present a new method, which we refer to as indirect two-sided relative ranking, for comparing gene expression profiles that is robust to variations in experimental conditions. This method extends the current best approach, which is based on comparing the correlations of the up and down regulated genes, by introducing a comparison based on the correlations in rankings across the entire database. Because our method is robust to experimental variations, it allows a greater variety of gene expression data to be combined, which, as we show, leads to richer scientific discoveries.</p> <p>Conclusions</p> <p>We demonstrate the benefit of our proposed indirect method on several datasets. We first evaluate the ability of the indirect method to retrieve compounds with similar therapeutic effects across known experimental barriers, namely vehicle and batch effects, on two independent datasets (one private and one public). We show that our indirect method is able to significantly improve upon the previous state-of-the-art method with a substantial improvement in recall at rank 10 of 97.03% and 49.44%, on each dataset, respectively. Next, we demonstrate that our indirect method results in improved accuracy for classification in several additional datasets. These datasets demonstrate the use of our indirect method for classifying cancer subtypes, predicting drug sensitivity/resistance, and classifying (related) cell types. Even in the absence of a known (i.e., labeled) experimental barrier, the improvement of the indirect method in each of these datasets is statistically significant.</p