Kelly Cho

A Mitochondrial Revelation of Early Human Migrations to the Tibetan Plateau Before and After the Last Glacial Maximum

As the highest plateau surrounded by towering mountain ranges, the Tibetan Plateau was once considered to be one of the last populated areas of modern humans. However, this view has been tremendously changed by archeological, linguistic, and genetic findings in the past 60 years. Nevertheless, the timing and routes of entry of modern humans into the Tibetan Plateau is still unclear. To make these problems clear, we carried out high-resolution mitochondrial-DNA (mtDNA) analyses on 562 Tibeto-Burman inhabitants from nine different regions across the plateau. By examining the mtDNA haplogroup distributions and their principal components, we demonstrated that maternal diversity on the plateau reflects mostly a northern East Asian ancestry. Furthermore, phylogeographic analysis of plateau-specific sublineages based on 31 complete mtDNA sequences revealed two primary components: pre-last glacial maximum (LGM) inhabitants and post-LGM immigrants. Also, the analysis of one major pre-LGM sublineage A10 showed a strong signal of post-LGM population expansion (about 15,000 years ago) and greater diversity in the southern part of the Tibetan Plateau, indicating the southern plateau as a refuge place when climate dramatically changed during LGM.

PPARG by dietary fat interaction influences bone mass in mice and humans

Adult BMD, an important risk factor for fracture, is the result of genetic and environmental interactions. A quantitative trait locus (QTL) for the phenotype of volumetric BMD (vBMD), named Bmd8, was found on mid‐distal chromosome (Chr) 6 in mice. This region is homologous to human Chr 3p25. The B6.C3H‐6T (6T) congenic mouse was previously created to study this QTL. Using block haplotyping of the 6T congenic region, expression analysis in the mouse, and examination of nonsynonymous SNPs, peroxisome proliferator activated receptor γ (Pparg) was determined to be the most likely candidate gene for the Bmd8 QTL of the 630 genes located in the congenic region. Furthermore, in the C3H/HeJ (C3H) strain, which is the donor strain for the 6T congenic, several polymorphisms were found in the Pparg gene. On challenge with a high‐fat diet, we found that the 6T mouse has a lower areal BMD (aBMD) and volume fraction of trabecular bone (BV/TV%) of the distal femur compared with B6 mice. Interactions between SNPs in the PPARG gene and dietary fat for the phenotype of BMD were examined in the Framingham Offspring Cohort. This analysis showed that there was a similar interaction of the PPARG gene and diet (fat intake) on aBMD in both men and women. These findings suggest that dietary fat has a significant influence on BMD that is dependent on the alleles present for the PPARG gene.

Genetic Landscape of Eurasia and “Admixture” in Uyghurs

To the Editor: In the papers1,2 by Xu and Jin, the genetic structure of Uyghurs was described by 8150 ancestry-informative markers (AIMs). These markers estimated the admixture rate of the Uyghur population to be around 50% East Asian ancestry by comparing Uyghurs to East Asians and Europeans. However, we suspect that the estimate of Xu and Jin may be considerably biased by insufficient reference population coverage. In their study, Xu and Jin used the STRUCTURE program3,4 as the major method for estimating the admixture rate; however, results from the STRUCTURE program are strictly the probabilities of assignment to different estimated clusters and therefore are influenced by both the marker selection and the populations used to estimate allele frequencies in those other clusters.

Prenatal exposure to nicotine and impaired reading performance

OBJECTIVE To investigate whether prenatal exposure to nicotine has an impact on several reading skill outcomes in school age children. STUDY DESIGN Using a longitudinal sample of 5119 school age children in the Avon Longitudinal Study of Parents and Children, this study investigated specific reading skill outcomes in the area of speed, fluency, accuracy, spelling, and comprehension in relation to prenatal nicotine exposure, after adjusting for potential mediators and confounders. Prenatal nicotine exposure was divided into 3 categories: high (>17 mg per day), low (≤17 mg per day), and no exposure. RESULTS We found that prenatal nicotine exposure was associated with increased risk of underperformance in specific reading skill outcomes after adjusting for potential mediators and confounders (P = .006). The effect of poor performance in decoding single words was most pronounced among children with prenatal exposure to high levels of nicotine in conjunction with a phonological deficit. Overall, the results showed that maternal smoking has moderate to large associations with delayed or decreased reading skills of children in the Longitudinal Study of Parents and Children. CONCLUSIONS High prenatal nicotine exposure has a negative association with reading performance in school age children. In addition, modeling showed that environmental factors significantly moderated the interaction between prenatal nicotine exposure and reading skill outcomes.

The Nuclear Transcription Factor PKNOX2 Is a Candidate Gene for Substance Dependence in European-Origin Women

Substance dependence or addiction is a complex environmental and genetic disorder that results in serious health and socio-economic consequences. Multiple substance dependence categories together, rather than any one individual addiction outcome, may explain the genetic variability of such disorder. In our study, we defined a composite substance dependence phenotype derived from six individual diagnoses: addiction to nicotine, alcohol, marijuana, cocaine, opiates or other drugs as a whole. Using data from several genomewide case-control studies, we identified a strong (Odds ratio  = 1.77) and significant (p-value = 7E-8) association signal with a novel gene, PBX/knotted 1 homeobox 2 (PKNOX2), on chromosome 11 with the composite phenotype in European-origin women. The association signal is not as significant when individual outcomes for addiction are considered, or in males or African-origin population. Our findings underscore the importance of considering multiple addiction types and the importance of considering population and gender stratification when analyzing data with heterogeneous population.

Refined QTLs of osteoporosis-related traits by linkage analysis with genome-wide SNPs: Framingham SHARe

Genome-wide association studies (GWAS) using high-density array of single-nucleotide polymorphisms (SNPs) offer an unbiased strategy to identify new candidate genes for osteoporosis. We used a subset of autosomal SNPs from the Affymetrix 500K+50K SNP GeneChip marker set to examine genetic linkage with multiple highly heritable osteoporosis-related traits, including BMD of the hip and spine, heel ultrasound (attenuation and speed of sound), and geometric indices of the hip, in two generations from the Framingham Osteoporosis Study. Variance component linkage analysis was performed using normalized residuals (adjusted for age, height, BMI, and estrogen status in women). Multipoint linkage analyses produced LOD scores > or =3.0 for BMD on chromosomes (chr.) 9 and 11 and for ultrasound speed of sound on chr. 5. Hip geometric traits were linked with higher LOD scores, such as with shaft width on chr. 4 (LOD=3.9) and chr. 16 (LOD=3.8) and with shaft section modulus on chr. 22 (LOD=4.0). LOD score > or =5.0 was obtained for femoral neck width on chr. 7. In conclusion, with an SNP-based linkage approach, we identified several novel potential QTLs and confirmed previously identified chromosomal regions linked to bone mass and geometry. Subsequent focus on the spectrum of genetic polymorphisms in these refined regions may contribute to finding variants predisposing to osteoporosis.

Detecting significant single-nucleotide polymorphisms in a rheumatoid arthritis study using random forests

Random forest is an efficient approach for investigating not only the effects of individual markers on a trait but also the effect of the interactions among the markers in genetic association studies. This approach is especially appealing for the analysis of genome-wide data, such as those obtained from gene expression/single-nucleotide polymorphism (SNP) array experiments in which the number of candidate genes/SNPs is vast. We applied this approach to the Genetic Analysis Workshop 16 Problem 1 data to identify SNPs that contribute to rheumatoid arthritis. The random forest computed a raw importance score for each SNP marker, where higher importance score suggests higher level of association between the marker and the trait. The significance level of the association was determined empirically by repeatedly reapplying the random forest on randomly generated data under the null hypothesis that no association exists between the markers and the trait. Using random forest, we were able to identify 228 significant SNPs (at the genome-wide significant level of 0.05) across the whole genome, over two-thirds of which are located on chromosome 6, especially clustered in the region of 6p21 containing the human leukocyte antigen (HLA) genes, such as gene HLA-DRB1 and HLA-DRA. Further analysis of this region indicates a strong association to the rheumatoid arthritis status.

Associations of Prenatal Nicotine Exposure and the Dopamine Related Genes ANKK1 and DRD2 to Verbal Language

Language impairment (LI) and reading disability (RD) are common pediatric neurobehavioral disorders that frequently co-occur, suggesting they share etiological determinants. Recently, our group identified prenatal nicotine exposure as a factor for RD and poor reading performance. Using smoking questionnaire and language data from the Avon Longitudinal Study of Parents and Children, we first determined if this risk could be expanded to other communication disorders by evaluating whether prenatal nicotine exposure increases risk for LI and poor performance on language tasks. Prenatal nicotine exposure increased LI risk (OR = 1.60; p = 0.0305) in a dose-response fashion with low (OR = 1.25; p = 0.1202) and high (OR = 3.84; p = 0.0002) exposures. Next, hypothesizing that the effects of prenatal nicotine may also implicate genes that function in nicotine related pathways, we determined whether known nicotine dependence (ND) genes associate with performance on language tasks. We assessed the association of 33 variants previously implicated in ND with LI and language abilities, finding association between ANKK1/DRD2 and performance on language tasks (p≤0.0003). The associations of markers within ANKK1 were replicated in a separate LI case-control cohort (p<0.05). Our results show that smoking during pregnancy increases the risk for LI and poor performance on language tasks and that ANKK1/DRD2 contributes to language performance. More precisely, these findings suggest that prenatal environmental factors influence in utero development of neural circuits vital to language. Our association of ANKK1/DRD2 further implicates the role of nicotine-related pathways and dopamine signaling in language processing, particularly in comprehension and phonological memory.

A genome-wide association analysis of Framingham Heart Study longitudinal data using multivariate adaptive splines

The Framingham Heart Study is a well known longitudinal cohort study. In recent years, the community-based Framingham Heart Study has embarked on genome-wide association studies. In this paper, we present a Framingham Heart Study genome-wide analysis for fasting triglycerides trait in the Genetic Analysis Workshop16 Problem 2 using multivariate adaptive splines for the analysis of longitudinal data (MASAL). With MASAL, we are able to perform analysis of genome-wide data with longitudinal phenotypes and covariates, making it possible to identify genes, gene-gene, and gene-environment (including time) interactions associated with the trait of interest. We conducted a permutation test to assess the associations between MASAL selected markers and triglycerides trait and report significant gene-gene and gene-environment interaction effects on the trait of interest.

Handling linkage disequilibrium in qualitative trait linkage analysis using dense SNPs: a two-step strategy

BackgroundIn affected sibling pair linkage analysis, the presence of linkage disequilibrium (LD) has been shown to lead to overestimation of the number of alleles shared identity-by-descent (IBD) among sibling pairs when parents are ungenotyped. This inflation results in spurious evidence for linkage even when the markers and the disease locus are not linked. In our study, we first theoretically evaluate how inflation in IBD probabilities leads to overestimation of a nonparametric linkage (NPL) statistic under the assumption of linkage equilibrium. Next, we propose a two-step processing strategy in order to systematically evaluate approaches to handle LD. Based on the observed inflation of expected logarithm of the odds ratio (LOD) from our theoretical exploration, we implemented our proposed two-step processing strategy. Step 1 involves three techniques to filter a dense set of markers. In step 2, we use the selected subset of markers from step 1 and apply four different methods of handling LD among dense markers: 1) marker thinning (MT); 2) recursive elimination; 3) SNPLINK; and 4) LD modeling approach in MERLIN. We evaluate relative performance of each method through simulation.ResultsWe observed LOD score inflation only when the parents were ungenotyped. For a given number of markers, all approaches evaluated for each type of LD threshold performed similarly; however, RE approach was the only one that eliminated the LOD score bias. Our simulation results indicate a reduction of approximately 75% to complete elimination of the LOD score inflation while maintaining the information content (IC) when setting a tolerable squared correlation coefficient LD threshold (r2) above 0.3 for or 2 SNPs per cM using MT.ConclusionWe have established a theoretical basis of how inflated IBD information among dense markers overestimates a NPL statistic. The two-step processing strategy serves as a useful framework to systematically evaluate relative performance of different methods to handle LD.