Z. Q. Zhang

Genome-wide association study suggested copy number variation may be associated with body mass index in the Chinese population

Obesity is a major public health problem characterized with high body mass index (BMI). Copy number variations (CNVs) have been identified to be associated with complex human diseases. The effect of CNVs on obesity is unknown. In this study, we explored the association of CNVs with BMI in 597 Chinese Han subjects using Affymetrix GeneChip Human Mapping 500K Array Set. We found that one CNV at 10q11.22 (from 46.36 Mb to 46.56 Mb) was associated with BMI (the raw P=0.011). The CNV contributed 1.6% of BMI variation, and it covered one important obesity gene—pancreatic polypeptide receptor 1(PPYR1). It was reported that PPYR1 was a key regulator of energy homeostasis. Our findings suggested that CNV might be potentially important for the BMI variation. In addition, our study suggested that CNV might be used as a genetic marker to locate genes associated with BMI in Chinese population.

Whole Genome Distribution and Ethnic Differentiation of Copy Number Variation in Caucasian and Asian Populations

Although copy number variation (CNV) has recently received much attention as a form of structure variation within the human genome, knowledge is still inadequate on fundamental CNV characteristics such as occurrence rate, genomic distribution and ethnic differentiation. In the present study, we used the Affymetrix GeneChip® Mapping 500K Array to discover and characterize CNVs in the human genome and to study ethnic differences of CNVs between Caucasians and Asians. Three thousand and nineteen CNVs, including 2381 CNVs in autosomes and 638 CNVs in X chromosome, from 985 Caucasian and 692 Asian individuals were identified, with a mean length of 296 kb. Among these CNVs, 190 had frequencies greater than 1% in at least one ethnic group, and 109 showed significant ethnic differences in frequencies (p<0.01). After merging overlapping CNVs, 1135 copy number variation regions (CNVRs), covering approximately 439 Mb (14.3%) of the human genome, were obtained. Our findings of ethnic differentiation of CNVs, along with the newly constructed CNV genomic map, extend our knowledge on the structural variation in the human genome and may furnish a basis for understanding the genomic differentiation of complex traits across ethnic groups.

The regulation-of-autophagy pathway may influence Chinese stature variation : evidence from elder adults

Recent success of genome-wide association studies (GWASs) on human height variation emphasized the effects of individual loci or genes. In this study, we used a developed pathway-based approach to further test biological pathways for potential association with stature, by examining ∼370 000 single-nucleotide polymorphisms (SNPs) across the human genome in 618 unrelated elder Han Chinese. A total of 626 biological pathways annotated by any of the three major public pathway databases (KEGG, BioCarta and Ambion GeneAssist Pathway Atlas) were tested. The regulation-of-autophagy (ROA) (nominal P=0.012) pathway was marginally significantly associated with human stature after our family wise error rate multiple-testing correction. We also used 1000 random recruited US whites for further replication. Interestingly, the ROA pathway presented the strongest signals in whites for height variation (nominal P=0.002). The results correspond to biological roles of the ROA pathway in human long bone development and growth. Our findings also implied that multiple-genetic factors may work jointly as a functional unit (pathway), and the traditional GWASs could have missed important genetic information imbedded in those less significant markers.

A genome wide association study between copy number variation (CNV) and human height in Chinese population.

Copy number variation (CNV) is a type of genetic variation which may have important roles in phenotypic variability and disease susceptibility. To hunt for genetic variants underlying human height variation, we performed a genome wide CNV association study for human height in 618 Chinese unrelated subjects using Affymetrix 500K array set. After adjusting for age and sex, we found that four CNVs at 6p21.3, 8p23.3-23.2, 9p23 and 16p12.1 were associated with human height (with borderline significant p value: 0.013, 0.011, 0.024, 0.049; respectively). However, after multiple tests correction, none of them was associated with human height. We observed that the gain of copy number (more than 2 copies) at 8p23.3-23.2 was associated with lower height (normal copy number vs. gain of copy number: 161.2 cm vs. 153.7 cm, p = 0.011), which accounted for 0.9% of height variation. Loss of copy number (less than 2 copies) at 6p21.3 was associated with 0.8% lower height (loss of copy number vs. normal copy number: 154.5 cm vs. 161.1 cm, p = 0.013). Since no important genes influencing height located in CNVs at loci of 8p23.3-23.2 and 6p21.3, the two CNVs may cause the structural rearrangements of neighbored important candidate genes, thus regulates the variation of height. Our results expand our knowledge of the genetic factors underlying height variation and the biological regulation of human height.

ON SOME ENRICHMENTS OF REPRODUCING KERNEL PARTICLE METHOD

In this paper efforts are made to enrich Reproducing Kernel Particle Method (RKPM). Firstly, the RKPM shape functions are expressed explicitly in terms of kernel function moments. This avoids numerical matrix inversions and solutions of linear algebraic equations which are involved in classical RKPM, and thus makes RKPM more accurate, faster and more efficient. Then, a recently developed truly meshless body integration technique is introduced into RKPM. It is based on a partition of unity by a set of overlapping patches covering the domain and eliminates background cells completely. We borrow an idea from computational geometry and propose a sweeping-line method to determine the quadrature points inside the domain. The method is robust and effective even for domain with complicated shapes. The truly meshless integration technique in combination with this sweeping-line method make implementation of RKPM quite simple, smart and especially very advantageous when nodes are irregularly scattered. Numerical results presented herein demonstrate that these enrichments make RKPM more efficient, versatile and particularly truly meshless.