Analysis of Sequence Data Under Multivariate Trait-Dependent Sampling

<div><p>High-throughput DNA sequencing allows for the genotyping of common and rare variants for genetic association studies. At the present time and for the foreseeable future, it is not economically feasible to sequence all individuals in a large cohort. A cost-effective strategy is to sequence those individuals with extreme values of a quantitative trait. We consider the design under which the sampling depends on multiple quantitative traits. Under such trait-dependent sampling, standard linear regression analysis can result in bias of parameter estimation, inflation of Type I error, and loss of power. We construct a likelihood function that properly reflects the sampling mechanism and uses all available data. We implement a computationally efficient EM algorithm and establish the theoretical properties of the resulting maximum likelihood estimators. Our methods can be used to perform separate inference on each trait or simultaneous inference on multiple traits. We pay special attention to gene-level association tests for rare variants. We demonstrate the superiority of the proposed methods over standard linear regression through extensive simulation studies. We provide applications to the Cohorts for Heart and Aging Research in Genomic Epidemiology Targeted Sequencing Study and the National Heart, Lung, and Blood Institute Exome Sequencing Project. Supplementary materials for this article are available online.</p></div

Percent body fat distributions for the 36 RNAi knock down Drosophila gene crosses, testing significantly different from corresponding Wild Type control, by Dunnett’s multiple comparisons test.

<p>Percent body fat distributions for the 36 RNAi knock down Drosophila gene crosses, testing significantly different from corresponding Wild Type control, by Dunnett’s multiple comparisons test.</p

Results of the functional drosophila screen for all genes nearby (± 250 kb) the 78 BMI-associated GWAS loci from speliotes et al. 2010[30] and locke et al. 2015[31].

<p>Results of the functional drosophila screen for all genes nearby (± 250 kb) the 78 BMI-associated GWAS loci from speliotes et al. 2010[<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007222#pgen.1007222.ref030" target="_blank">30</a>] and locke et al. 2015[<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007222#pgen.1007222.ref031" target="_blank">31</a>].</p

Summary of Drosophila functional scan for the 61 BMI GWAS loci that could be tested in the fly.

<p>Number of GWAS BMI loci for which nearby genes were validated in RNAi KDs in Drosophila. <b>(a)</b> Distribution of Number of Significant Fly KD Genes per BMI Locus Region. Significance determined by Dunnett’s Multiple Comparisons Test. <b>(b)</b> Number of Significant Fly KD Genes per BMI Locus by Proximity to SNP. Significance determined by Dunnett’s Multiple Comparisons Test. CNBT = Could Not Be Tested in Fly (either No Fly Ortholog or KD lethal).</p

Percent body fat distributions for the 36 RNAi knock down Drosophila gene crosses, testing significantly different from corresponding Wild Type control, by Dunnett’s multiple comparisons test.

<p>Percent body fat distributions for the 36 RNAi knock down Drosophila gene crosses, testing significantly different from corresponding Wild Type control, by Dunnett’s multiple comparisons test.</p

Experimental design of the Drosophila BMI loci functional screen.

<p>WT = Corresponding RNAi Wild Type (as detailed in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007222#pgen.1007222.g003" target="_blank">Fig 3</a>).</p

Genetic Determinants of Pelvic Organ Prolapse among African American and Hispanic Women in the Women’s Health Initiative

<div><p>Current evidence suggests a multifactorial etiology to pelvic organ prolapse (POP), including genetic predisposition. We conducted a genome-wide association study of POP in African American (AA) and Hispanic (HP) women from the Women’s Health Initiative Hormone Therapy study. Cases were defined as any POP (grades 1–3) or moderate/severe POP (grades 2–3), while controls had grade 0 POP. We performed race-specific multiple logistic regression analyses between SNPs imputed to 1000 genomes in relation to POP (grade 0 vs 1–3; grade 0 vs 2–3) adjusting for age at diagnosis, body mass index, parity, and genetic ancestry. There were 1274 controls and 1427 cases of any POP and 317 cases of moderate/severe POP. Although none of the analyses reached genome-wide significance (p<5x10^-8), we noted variants in several loci that met p<10⁻⁶. In race-specific analysis of grade 0 vs 2–3, intronic SNPs in the <i>CPE</i> gene (rs28573326, OR:2.14; 95% CI 1.62–2.83; p = 1.0x10^-7) were associated with POP in AAs, and SNPs in the gene <i>AL132709</i>.<i>5</i> (rs1950626, OR:2.96; 95% CI 1.96–4.48, p = 2.6x10^-7) were associated with POP in HPs. Inverse variance fixed-effect meta-analysis of the race-specific results showed suggestive signals for SNPs in the <i>DPP6</i> gene (rs11243354, OR:1.36; p = 4.2x10^-7) in the grade 0 vs 1–3 analyses and for SNPs around <i>PGBD5</i> (rs740494, OR:2.17; p = 8.6x10^-7) and <i>SHC3</i> (rs2209875, OR:0.60; p = 9.3x10^-7) in the grade 0 vs 2–3 analyses. While we did not identify genome-wide significant findings, we document several SNPs reaching suggestive statistical significance. Further interrogation of POP in larger minority samples is warranted.</p></div

Admixture mapping of pelvic organ prolapse in African Americans from the Women’s Health Initiative Hormone Therapy trial

<div><p>Evidence suggests European American (EA) women have two- to five-fold increased odds of having pelvic organ prolapse (POP) when compared with African American (AA) women. However, the role of genetic ancestry in relation to POP risk is not clear. Here we evaluate the association between genetic ancestry and POP in AA women from the Women’s Health Initiative Hormone Therapy trial. Women with grade 1 or higher classification, and grade 2 or higher classification for uterine prolapse, cystocele or rectocele at baseline or during follow-up were considered to have any POP (N = 805) and moderate/severe POP (N = 156), respectively. Women with at least two pelvic exams with no indication for POP served as controls (N = 344). We performed case-only, and case-control admixture-mapping analyses using multiple logistic regression while adjusting for age, BMI, parity and global ancestry. We evaluated the association between global ancestry and POP using multiple logistic regression. European ancestry at the individual level was not associated with POP risk. Case-only and case-control local ancestry analyses identified two ancestry-specific loci that may be associated with POP. One locus (Chromosome 15q26.2) achieved empirically-estimated statistical significance and was associated with decreased POP odds (considering grade ≥2 POP) with each unit increase in European ancestry (OR: 0.35; 95% CI: 0.30, 0.57; p-value = 1.48x10^-5). This region includes <i>RGMA</i>, a potent regulator of the BMP family of genes. The second locus (Chromosome 1q42.1-q42.3) was associated with increased POP odds with each unit increase in European ancestry (Odds ratio [OR]: 1.69; 95% confidence interval [CI]: 1.28, 2.22; p-value = 1.93x10^-4). Although this region did not reach statistical significance after considering multiple comparisons, it includes potentially relevant genes including <i>TBCE</i>, and <i>ACTA1</i>. Unique non-overlapping European and African ancestry-specific susceptibility loci may be associated with increased POP risk.</p></div

Figure 1

<p>Kaplan-Meier survival curves for 1) study subjects with lower serum total homocysteine (tHcy<11.28 µmol/L) and no <i>COMT</i> Met158Met genotype, 2) study subjects with higher serum tHcy (≥11.28 µmol/L) and no <i>COMT</i> Met158Met genotype, 3) study subjects with lower serum tHcy and <i>COMT</i> Met158Met genotype, and 4) study subjects with higher serum tHcy and <i>COMT</i> Met158Met genotype.</p

Characteristics of the study subjects according to the catechol-o-methyltransferase (<i>COMT</i>) genotypes^*

<p>Abbreviations: BMI = body mass index; HDL = high density lipoprotein; IHD = ischemic heart disease; LDL = low density lipoprotein; tHcy = total homocysteine concentration.</p>*<p>Data are expressed as the mean±SD unless otherwise indicated.</p