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Observational studies have revealed phenotypic associations between type 2 diabetes (T2D) and many biomarkers. However, causality between these conditions in East Asians is unclear. We leveraged genome-wide association study (GWAS) summary statistics on T2D (n  = 77,418 cases; n  = 356,122 controls) from the Asian Genetic Epidemiology Network (sample recruited during 2001–2011) and GWAS summary statistics on 42 biomarkers (n  = 12,303–143,658) from BioBank Japan (sample recruited during 2003–2008) to investigate causal relationships between T2D and biomarkers. Applications of Mendelian randomization approaches consistently revealed genetically instrumented associations of T2D with increased serum potassium levels (liability-scale β = 0.04–0.10; P  = 6.41 × 10−17–9.85 × 10−5) and decreased serum chloride levels (liability-scale β = −0.16 to −0.06; P  = 5.22 × 10−27–3.14 × 10−5), whereas these 2 biomarkers showed no causal effects on T2D. Heritability Estimation Using Summary Statistics (ρ-HESS) and summary-data–based Mendelian randomization highlighted 27 genomic regions and 3 genes (α-1,3-mannosyl-glycoprotein 2-β- N -acetylglucosaminyltransferase (MGAT1), transducing-like enhancer (TLE) family member 1, transcriptional corepressor (TLE1), and 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR)) that interactively associated with the shared genetics underlying T2D and the 2 biomarkers. Thus, T2D may causally affect serum potassium and chloride levels among East Asians. In contrast, the relationships of potassium and chloride with T2D are not causal, suggesting the importance of monitoring electrolyte disorders for T2D patients. [ABSTRACT FROM AUTHOR]

Breast cancer (BC), a heterogeneous, aggressive illness with high mortality, is essentially a genomic disease. While the high-penetrance genes BRCA1 and BRCA2 play important roles in tumorigenesis, moderate- and low-penetrance genes are also involved. Single-nucleotide polymorphisms (SNPs) in microRNA (miRNA) genes have recently been identified as BC risk factors. miRNA genes are currently classified as low-penetrance. SNPs are the most common variations in the human genome. While the role of miRNA SNPs in BC susceptibility has been studied extensively, results have been inconsistent. This review analyzes the results of association studies between miRNA SNPs and BC risk from countries around the world. We conclude that: (a) By continent, the largest proportion of studies to date were conducted in Asia (65.0 %) and the smallest proportion in Africa (1.8 %); (b) Association studies have been completed for 67 different SNPs; (c) 146a, 196a2, 499, 27a, and 423 are the most-studied miRNAs; (d) The SNPs rs2910164 (miRNA-146a), rs11614913 (miRNA-196a2), rs3746444 (miRNA-499) and rs6505162 (miRNA-423) were the most widely associated with increased BC risk; (e) The majority of studies had small samples, which may affect the precision and power of the results; and (f) The effect of an SNP on BC risk depends on the ethnicity of the population. This review also discusses potential explanations for controversial findings. [ABSTRACT FROM AUTHOR]

Most large population-based genomic studies have, until now, mainly focused on European ancestral populations. The Singapore-based GenomeAsia100K (GA100K) Consortium aims to address this bias by targeting major Asian populations and generating reference genomes for various ethnic groups. GA100K is also studying historical population migrations and providing bioinformatic tools that may help tackle diseases among Asia's multi-ethnic populations. These project goals transcend national boundaries, national genome projects, localized national science, and medicine. Rather, GA100K leverages the strategic location of Singapore as a regional nexus to advance science and technology within Singapore. GA100K is thus symptomatic of the Singaporean nation-state's ambition to be a knowledge-based economy and a regional biomedical hub. This article thus speaks to literature in STS that deals with the interface and entanglements of human tissue biobanks, human genome projects, and national development. [ABSTRACT FROM AUTHOR]

The author explores the study of genomes of indigenous communities in the Pacific. She reflects on her interest in studying human DNA in order to understand human history and human diversity. She recalls her experience of using mitochondrial DNA (mtDNA) phylogenies of commensal animals to track human migration. She also expresses her concerns over the use or misuse of genetic data.

Background Genetic differences in the target proteins, metabolizing enzymes and transporters that contribute to inter-individual differences in drug response are not integrated in contemporary drug development programs. Ayurveda, that has propelled many drug discovery programs albeit for the search of new chemical entities incorporates inter-individual variability “ Prakriti ” in development and administration of drug in an individualized manner. Prakriti of an individual largely determines responsiveness to external environment including drugs as well as susceptibility to diseases. Prakriti has also been shown to have molecular and genomic correlates. We highlight how integration of Prakriti concepts can augment the efficiency of drug discovery and development programs through a unique initiative of Ayurgenomics TRISUTRA consortium. Methods Five aspects that have been carried out are (1) analysis of variability in FDA approved pharmacogenomics genes/SNPs in exomes of 72 healthy individuals including predominant Prakriti types and matched controls from a North Indian Indo-European cohort (2) establishment of a consortium network and development of five genetically homogeneous cohorts from diverse ethnic and geo-climatic background (3) identification of parameters and development of uniform standard protocols for objective assessment of Prakriti types (4) development of protocols for Prakriti evaluation and its application in more than 7500 individuals in the five cohorts (5) Development of data and sample repository and integrative omics pipelines for identification of genomic correlates. Results Highlight of the study are (1) Exome sequencing revealed significant differences between Prakriti types in 28 SNPs of 11 FDA approved genes of pharmacogenomics relevance viz. CYP2C19, CYP2B6, ESR1, F2, PGR, HLA-B, HLA-DQA1, HLA-DRB1, LDLR, CFTR, CPS1. These variations are polymorphic in diverse Indian and world populations included in 1000 genomes project. (2) Based on the phenotypic attributes of Prakriti we identified anthropometry for anatomical features, biophysical parameters for skin types, HRV for autonomic function tests, spirometry for vital capacity and gustometry for taste thresholds as objective parameters. (3) Comparison of Prakriti phenotypes across different ethnic, age and gender groups led to identification of invariant features as well as some that require weighted considerations across the cohorts. Conclusion Considering the molecular and genomics differences underlying Prakriti and relevance in disease pharmacogenomics studies, this novel integrative platform would help in identification of differently susceptible and drug responsive population. Additionally, integrated analysis of phenomic and genomic variations would not only allow identification of clinical and genomic markers of Prakriti for application in personalized medicine but also its integration in drug discovery and development programs. [ABSTRACT FROM AUTHOR]

High-throughput sequencing technology enables population-level surveys of human genomic variation. Here, we examine the joint allele frequency distributions across continental human populations and present an approach for combining complementary aspects of whole-genome, low-coverage data and targeted high-coverage data. We apply this approach to data generated by the pilot phase of the Thousand Genomes Project, including whole-genome 2-4× coverage data for 179 samples from HapMap European, Asian, and African panels as well as high-coverage target sequencing of the exons of 800 genes from 697 individuals in seven populations. We use the site frequency spectra obtained from these data to infer demographic parameters for an Out-of-Africa model for populations of African, European, and Asian descent and to predict, by a jackknife-based approach, the amount of genetic diversity that will be discovered as sample sizes are increased. We predict that the number of discovered nonsynonymous coding variants will reach 100,000 in each population after ∼1,000 sequenced chromosomes per population, whereas ∼2,500 chromosomes will be needed for the same number of synonymous variants. Beyond this point, the number of segregating sites in the European and Asian panel populations is expected to overcome that of the African panel because of faster recent population growth. Overall, we find that the majority of human genomic variable sites are rare and exhibit little sharing among diverged populations. Our results emphasize that replication of disease association for specific rare genetic variants across diverged populations must overcome both reduced statistical power because of rarity and higher population divergence. [ABSTRACT FROM AUTHOR]

Objectives: R483 is a thiazolidinedione peroxisome proliferator-activated receptor gamma (PPARγ) agonist with anti-diabetic properties and also a cytochrome P450 2C19 (CYP2C19) substrate. The aim of the clinical studies reported here was to investigate the influence of the CYP2C19 genotype on the pharmacokinetics (PK) of R483 in healthy subjects and in type 2 diabetes mellitus (T2DM) patients. Methods: Data came from two clinical studies, one including 58 Japanese and Caucasian healthy subjects and another including 93 Asian T2DM patients. All subjects received multiple doses of R483, 20 mg once daily for the healthy subjects and 12 mg once daily for the T2DM patients. Blood samples were taken up to 24 h after the last dose to determine plasma concentrations of R483 and its major metabolites. Results: Poor metabolizers (PMs; CYP2C19*2/*2 or *2/*3 or *3/*3) had a higher plasma exposure and a lower clearance of the parent drug than extensive metabolizers (EMs; CYP2C19*1/*1 or *1/*2 or *1/*3). The homozygous PM/EM ratio for the area under the plasma concentration-time curve (AUC) [95% confidence interval] was 3.9 [2.7-5.7] for healthy subjects versus 2.0 [1.5-2.6] in T2DM patients. The heterozygous EMs were all T2DM patients, the PM/EM ratio for AUC was 1.5 [1.2-1.8]. The dose-normalized exposure to R483 was 1.2- (for PMs) and 2.4-fold (for EMs) higher in T2DM patients than in healthy subjects. R483 was well tolerated in both studies. Conclusions: The plasma exposure to R483 was significantly higher in PMs than in EMs. R483 exhibits different PK in healthy subjects and T2DM patients, and the difference in exposure between EM and PM was less pronounced in T2DM patients than in healthy subjects. Factors such as diabetes condition and age may influence the metabolism of R483. This knowledge allowed for a realistic dose recommendation for poor metabolizer T2DM patients. [ABSTRACT FROM AUTHOR]

Copy number variation (CNV) of DNA sequences is functionally significant but has yet to be fully ascertained. We have constructed a first-generation CNV map of the human genome through the study of 270 individuals from four populations with ancestry in Europe, Africa or Asia (the HapMap collection). DNA from these individuals was screened for CNV using two complementary technologies: single-nucleotide polymorphism (SNP) genotyping arrays, and clone-based comparative genomic hybridization. A total of 1,447 copy number variable regions (CNVRs), which can encompass overlapping or adjacent gains or losses, covering 360 megabases (12% of the genome) were identified in these populations. These CNVRs contained hundreds of genes, disease loci, functional elements and segmental duplications. Notably, the CNVRs encompassed more nucleotide content per genome than SNPs, underscoring the importance of CNV in genetic diversity and evolution. The data obtained delineate linkage disequilibrium patterns for many CNVs, and reveal marked variation in copy number among populations. We also demonstrate the utility of this resource for genetic disease studies. [ABSTRACT FROM AUTHOR]

One of the major questions in human genetics is what percentage of individuals in the general population carry a disease-causing mutation. Based on publicly available information on genotypes from six main world populations, we created a database including data on 276,921 sequence variants, present within 187 genes associated with autosomal recessive (AR) inherited retinal diseases (IRDs). Assessment of these variants revealed that 10,044 were categorized as disease-causing mutations. We developed an algorithm to compute the gene-specific prevalence of disease, as well as the mutational burden in healthy subjects. We found that the genetic prevalence of AR-IRDs corresponds approximately to 1 case in 1,380 individuals, with 5.5 million people expected to be affected worldwide. In addition, we calculated that unaffected carriers of mutations are numerous, ranging from 1 in 2.26 individuals in Europeans to 1 in 3.50 individuals in the Finnish population. Our analysis indicates that about 2.7 billion people worldwide (36% of the population) are healthy carriers of at least one mutation that can cause AR-IRD, a value that is probably the highest across any group of Mendelian conditions in humans., Competing Interests: The authors declare no competing interest.

States that job opportunities for scientists in Asia are growing. Demand for those with a business background as strong; Aspects of the Asian economic crisis; Taiwan's efforts to build science parks that are a major source of employment; Prospects for those scientists in the field of genomics; Commercial opportunities; Poor salaries for scientists in the public sector seen as prohibitive; Short-stay visits of the National Natural Science Foundation of China which provides small project grants. INSETS: New blood for chinese academy;Tsinghua University recruits for excellence;Openings in human genome research in China, Swinbanks & Nathan.

Next-generation massively parallel DNA sequencing technologies provide ultrahigh throughput at a substantially lower unit data cost; however, the data are very short read length sequences, making de novo assembly extremely challenging. Here, we describe a novel method for de novo assembly of large genomes from short read sequences. We successfully assembled both the Asian and African human genome sequences, achieving an N50 contig size of 7.4 and 5.9 kilobases (kb) and scaffold of 446.3 and 61.9 kb, respectively. The development of this de novo short read assembly method creates new opportunities for building reference sequences and carrying out accurate analyses of unexplored genomes in a cost-effective way. [ABSTRACT FROM AUTHOR]

We report an analysis of more than 240,000 loci genotyped using the Affymetrix SNP microarray in 554 individuals from 27 worldwide populations in Africa, Asia, and Europe. To provide a more extensive and complete sampling of human genetic variation, we have included caste and tribal samples from two states in South India, Daghestanis from eastern Europe, and the Iban from Malaysia. Consistent with observations made by Charles Darwin, our results highlight shared variation among human populations and demonstrate that much genetic variation is geographically continuous. At the same time, principal components analyses reveal discernible genetic differentiation among almost all identified populations in our sample, and in most cases, individuals can be clearly assigned to defined populations on the basis of SNP genotypes. All individuals are accurately classified into continental groups using a model-based clustering algorithm, but between closely related populations, genetic and self-classifications conflict for some individuals. The 250K data permitted high-level resolution of genetic variation among Indian caste and tribal populations and between highland and lowland Daghestani populations. In particular, upper-caste individuals from Tamil Nadu and Andhra Pradesh form one defined group, lower-caste individuals from these two states form another, and the tribal Irula samples form a third. Our results emphasize the correlation of genetic and geographic distances and highlight other elements, including social factors that have contributed to population structure. [ABSTRACT FROM AUTHOR]