Multiple-marker Test Research Articles

BRASS: Permutation methods for binary traits in genetic association studies with structured samples.

In genetic association analysis of complex traits, permutation testing can be a valuable tool for assessing significance when the distribution of the test statistic is unknown or not well-approximated. This commonly arises, e.g, in tests of gene-set, pathway or genome-wide significance, or when the statistic is formed by machine learning or data adaptive methods. Existing applications include eQTL mapping, association testing with rare variants, inclusion of admixed individuals in genetic association analysis, and epistasis detection among many others. For genetic association testing in samples with population structure and/or relatedness, use of naive permutation can lead to inflated type 1 error. To address this in quantitative traits, the MVNpermute method was developed. However, for association mapping of a binary trait, the relationship between the mean and variance makes both naive permutation and the MVNpermute method invalid. We propose BRASS, a permutation method for binary traits, for use in association mapping in structured samples. In addition to modeling structure in the sample, BRASS allows for covariates, ascertainment and simultaneous testing of multiple markers, and it accommodates a wide range of test statistics. In simulation studies, we compare BRASS to other permutation and resampling-based methods in a range of scenarios that include population structure, familial relatedness, ascertainment and phenotype model misspecification. In these settings, we demonstrate the superior control of type 1 error by BRASS compared to the other 6 methods considered. We apply BRASS to assess genome-wide significance for association analyses in domestic dog for elbow dysplasia (ED) and idiopathic epilepsy (IE). For both traits we detect previously identified associations, and in addition, for ED, we detect significant association with a SNP on chromosome 35 that was not detected by previous analyses, demonstrating the potential of the method.

Validation of a multiple marker test for early pregnancy outcome prediction.

To validate the use of a multiple biomarker test panel for predicting first trimester pregnancy outcome in a multi-center cohort. A case-control study of women presenting with pain and bleeding in early pregnancy at 5-10 weeks gestational age was performed at three academic centers. Sera from women with ectopic pregnancy (EP), viable intrauterine pregnancy (IUP), and miscarriage (SAB) were analyzed via immunoassay for Activin A (AA), Progesterone (P4), A Disintegrin And Metalloprotease-12 (ADAM12), pregnancy-associated plasma protein A (PAPP-A), glycodelin (Glyc), and human chorionic gonadotropin (hCG). Biomarkers were assessed for reproducibility using medians, ranges, standard deviations, and area under receiver-operating characteristic curve (AUC) and accuracy in early pregnancy outcome classification compared to a previous derivation population. In 192 pregnancies, the biomarkers demonstrated good reproducibility with similar medians, ranges, and AUCs when compared to the derivation population except glycodelin. Pregnancy location was conclusively classified in 53% (n = 94) of the whole study sample with 78% accuracy. Pregnancy viability was conclusively classified in 58% (n = 112) of the new sample with 89% accuracy. Results were similar with subsequent model revisions where glycodelin was excluded and in the subgroups of subjects with a hCG below 2000 mIU/mL and a gestational age less than 6 weeks. The use of a panel of biomarkers to maximize test accuracy of a prediction of pregnancy location and prediction of pregnancy viability was reproducible and validated in an external population from which it was derived, but clinical utility is limited based on the test characteristics obtained.

Comprehensive Application of Multiple Genetic Markers in a Case of Half-Siblings With the Same Father and Different Mothers and an Avuncular Relationship

Half-sibling (HS) kinship testing is more difficult and complicated. This article describes a case where we sought to establish if three children with different mothers (one boy and two girls), shared a common father. The three children and their mother, as well as the suspected father's elder brother took part in the identification. To investigate the application of multiple genetic markers in HS kinship testing, autosomal STR, Y-STR, and X-STR was performed on blood samples from the individuals of interest C1 (female), M1 (mother of C1), C2 (male), M2 (mother of C2), C3 (female), M3 (mother of C3), and UC (elder brother of the suspected biological father). The 24 Y-STR haplotypes of C2 and UC were identical, confirming that they come from the same paternal line. Among the 27 X-STRs tested in C1 and C3, 18 of them had different paternal alleles, so C1 and C3 were excluded as half-sibling kinship.39 autosomal STR were calculated by ITO method, the HSI (or AI) of the pairs C1–C3, C2–C3, and C3–UC are <1, so HS kinship between C1 and C3, and between C2 and C3 can be excluded and avuncular kinship between C3 and UC can be excluded. The HSI (or AI) of the pairs C1–C2, C1–UC, and C2–UC are much >1, which may supports HS kinship between C1 and C2 and avuncular kinship between C1 and UC, and between C2 and UC.15 autosomal STR were calculated by discriminant function, DHS3 > DR3 between C1 and C2, and thus they could be HS. DHS3 < DR3 between C1 and C3, and between C2 and C3, so C1 and C3, and C2 and C3 may be unrelated individuals. Based on the above results, we can conclude that a HS relationship may be existed between C1 and C2. There may be a avuncular relationships between C1 and UC and between C2 and UC. HS relationships between C3 and C1 and between C3 and C2 as well as an avuncular relationship between C3 and UC were not supported by this study. The application of multiple genetic marker testing should be more regularly applied in the evaluation of HS and avuncular relationships. Increasing the number of related individuals tested when evaluating kinship relationships provides more data for better identification.

Exploring the Structural Link Between FOXP2 and ADHD in Human Adults

The forkhead box protein P2 (FOXP2) gene, located on chromosome 7, codes for a forkhead/winged‐helix transcription factor which regulates transcript production, typically repressing expression of neutral targets. The Olathe North MSOE Center for BioMolecular Modeling SMART Team used 3‐D modeling and printing technology to examine the structure‐function relationship between this protein, FOXP2, and attention deficit hyperactivity disorder (ADHD) in human adults. An assessment of the relationship between the presence of each of 12 FOXP2 tagSNPs and the presence of ADHD in two European samples found 1 tagSNP to be significantly associated with combined ADHD in one sample in both a single‐ and multiple‐marker test. These encouraging results provided the foundation for further exploration of the structural link between FOXP2 and ADHD in adults. Current studies involve observation of a variety of samples and deep‐sequencing of the FOXP2 genomic region with the intent to identify the sequence variants directly involved in the genetic background of ADHD. Future studies may focus on genes regulating and regulated by FOXP2 to gain a better understanding of the mechanisms and functions of the protein.Support or Funding InformationThe Olathe North MSOE Center for BioMolecular Modeling SMART Team used 3‐D modeling and printing technology to examine the structure‐function relationship between this protein, FOXP2, and ADHD in human adults.Sponsors: Chris Elniff and L.B. FogtMentor: Brendan Mattingly, University of Kansas Edwards

Use of multiple inflammatory marker tests in primary care: using Clinical Practice Research Datalink to evaluate accuracy.

BackgroundResearch comparing C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), and plasma viscosity (PV) in primary care is lacking. Clinicians often test multiple inflammatory markers, leading to concerns about overuse.AimTo compare the diagnostic accuracies of CRP, ESR, and PV, and to evaluate whether measuring two inflammatory markers increases accuracy.Design and settingProspective cohort study in UK primary care using the Clinical Practice Research Datalink.MethodThe authors compared diagnostic test performance of inflammatory markers, singly and paired, for relevant disease, defined as any infections, autoimmune conditions, or cancers. For each of the three tests (CRP, ESR, and PV), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under receiver operator curve (AUC) were calculated.ResultsParticipants comprised 136 961 patients with inflammatory marker testing in 2014; 83 761 (61.2%) had a single inflammatory marker at the index date, and 53 200 (38.8%) had multiple inflammatory markers. For ‘any relevant disease’, small differences were seen between the three tests; AUC ranged from 0.659 to 0.682. CRP had the highest overall AUC, largely because of marginally superior performance in infection (AUC CRP 0.617, versus ESR 0.589, P<0.001). Adding a second test gave limited improvement in the AUC for relevant disease (CRP 0.682, versus CRP plus ESR 0.688, P<0.001); this is of debatable clinical significance. The NPV for any single inflammatory marker was 94% compared with 94.1% for multiple negative tests.ConclusionTesting multiple inflammatory markers simultaneously does not increase ability to rule out disease and should generally be avoided. CRP has marginally superior diagnostic accuracy for infections, and is equivalent for autoimmune conditions and cancers, so should generally be the first-line test.

Multiplex quantitative imaging of human myocardial infarction by mass spectrometry-immunohistochemistry.

Simultaneous assessment of a panel of protein markers is becoming essential in order to enhance biomarker research and improve diagnostics. Specifically, postmortem diagnostics of early myocardial ischemia in sudden cardiac death cases could benefit from a multiplex marker assessment in the same tissue section. Current analytical antibody-based techniques (immunohistochemistry and immunofluorescence) limit multiplex analysis usually to not more than three antibodies. In this study, mass spectrometry-immunohistochemistry (MS-IHC) was performed by combining laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) with rare-metal-isotope-tagged antibodies as a technique for multiplex analysis of human postmortem myocardial tissue samples. Tissue sections with myocardial infarction were simultaneously analyzed for seven primary, rare-metal-isotope-tagged antibodies (troponin T, myoglobin, fibronectin, C5b-9, unphosphorylated connexin 43, VEGF-B, and JunB). Comparison between the MS-IHC approach and chromogenic IHC showed similar patterns in ionic and optical images. In addition, absolute quantification was performed by MS-IHC, providing a proportional relationship between the signal intensity and the local marker concentration in tissue sections. These data demonstrated that LA-ICP-MS combined with rare-metal-isotope-tagged antibodies is an efficient strategy for simultaneous testing of multiple markers and allows not only visualization of molecules within the tissue but also quantification of the signal. Such imaging approach has a great potential in both diagnostics and pathology-related research.

Genetic basis of Lipomatous Myopathy in Piedmontese beef cattle

Abstract In Piedmontese cattle breed, the sporadic detection of Lipomatous Myopathy (LM) has been reported. The phenotypic disease expression consists in degeneration and infiltration of the muscular tissue characterized by replacement of myofibers with adipose tissue. The aim of this study was to investigate the existence of genetic loci associated with lipomatous myopathy in Piedmontese cattle breed through a genome wide association study based on a DNA pooling design. The samples used for the study were collected from a meat cutting plant, pairing cases and controls within farms. Samples of different muscles (diaphragm, superficial and deep pectoral, intercostal, sternocleidomastoid group and vastus lateralis ) were histopathologically and enzymatically classified as cases and controls. DNA pools of cases and controls were constructed. Equal amounts of DNA were pooled from individuals for the constitution of 4 pools (2 independent biological replicates for cases and 2 for controls). Technical duplicates were also built and all pools genotyped with the Illumina BovineHD BeadChip three time each, for a total of 24 chip array positions. SNPs positions were based on the UMB 3.1 bovine assembly. The B-allele frequencies (BAF) for each array replicate were used in a specific pipeline in R software to perform multiple marker tests after excluding the 5% of SNPs showing the highest BAF variability from the replicate arrays within tail, as well as the monomorphic SNPs. A total of 41 QTLRs were identified on the 29 bovine autosomes, and 4 on the X chromosome. A subset of the identified markers fall inside or nearby genes involved in myogenesis, adipogenesis and cell to cell adhesions. The biological role of these genes in the onset of lipomatous myopathy has been identified looking at the known functions of the encoded proteins on the GeneCards database. Gene networks have been identified using STRING.

Predicting first trimester pregnancy outcome: derivation of a multiple marker test.

To predict first trimester pregnancy outcome using biomarkers in a multicenter cohort. Case-control study. Three academic centers. Women with pain and bleeding in early pregnancy. Sera from women who were 5-12weeks' gestational age with ectopic pregnancy (EP), viable intrauterine pregnancy (IUP), and miscarriage/spontaneous abortion (SAB) was analyzed by ELISA and immunoassay for activin A, inhibin A, P, A Disintegrin And Metalloprotease-12, pregnancy-associated plasma protein A (PAPP-A), pregnancy specific B1-glycoprotein (SP1), placental-like growth factor, vascular endothelial growth factor, glycodelin (Glyc), and hCG. Classification trees were developed to optimize sensitivity/specificity for pregnancy location and viability. Area under receiver operating characteristic curve, sensitivity, specificity, and accuracy of first trimester pregnancy outcome. In 230 pregnancies, the combination of trees to maximize sensitivity and specificity resulted in 73% specificity (95% confidence interval (CI) 0.65-0.80) and 31% sensitivity (95% CI 0.21-0.43) for viability. Similar methods had 21% sensitivity (95% CI 0.12-0.32) and 33% specificity (95% CI 0.26-0.41) for location. Activin A, Glyc, and A Disintegrin And Metalloprotease-12 definitively classified pregnancy location in 29% of the sample with 100% accuracy for EP. Progesterone and PAPP-A classified the viability in 61% of the sample with 94% accuracy. Multiple marker panels can distinguish pregnancy location and viability in a subset of women at risk for early pregnancy complications. This strategy of combining markers to maximize sensitivity and specificity results in high accuracy in a subset of subjects. Activin A, ADAM12, and Glyc are the most promising markers for pregnancy location; P and PAPP-A for viability.

Aneuploidy Screening in Pregnancy.

Prenatal aneuploidy screening has changed dramatically in recent years with increases in the types of chromosomal abnormalities reliably identified and in the proportion of aneuploid fetuses detected. Initially, screening was available only for trisomies 21 and 18 and was offered only to low-risk pregnancies. Improved detection with the quadruple- and first-trimester multiple marker screens led to the option of aneuploidy screening for women 35 years of age and older. Cell-free DNA tests now screen for common autosomal trisomies and sex chromosome aneuploidies. Cell-free DNA screening is particularly effective in older women because of higher positive predictive values and lower false-positive rates. Integrated first- and second-trimester multiple marker tests provide specific risks for trisomies 21, 18, and possibly 13, and may detect an even wider range of aneuploidies. Given current precision in risk assessment, based on maternal age and preferences for screening or diagnostic tests, counseling has become more complex. This review addresses the benefits and limitations of available aneuploidy screening methods along with counseling considerations when offering them.

Predicting early pregnancy outcome: a multiple marker test

Predicting early pregnancy outcome: a multiple marker test

Development of a Multiple Marker Test for Ectopic Pregnancy

Although ultrasound is currently the standard of care used to diagnose ectopic pregnancy, it often requires multiple examinations and weeks to make a definitive diagnosis. Thus, this case-control study attempted to identify an optimal combination of biomarkers that can be used to identify ectopic pregnancy. Data were gathered from September 2000 to April 2009 using serum from the Ectopic Pregnancy Biomarkers Bank protocol. Sera were collected from women who presented to one of three emergency departments with pain, vaginal bleeding, or both, and who had a positive pregnancy test but were<12 weeks gestation.

Development of a Multiple Marker Test for Ectopic Pregnancy

Many serum markers have been proposed to aid in the identification of an ectopic pregnancy, but few have been validated. Most studies have been limited by sample size and design. The goal of this study was to assess putative markers to identify which can be optimally combined. We conducted a case-control study using sera from 100 patients with ectopic pregnancy and 100 patients with intrauterine pregnancy who presented to three urban academic centers between September 2000 and April 2009 with first-trimester pain or bleeding. Samples were analyzed for 12 promising biomarkers. Classification tree analysis was used to examine markers simultaneously with the goal of optimizing the accuracy of ectopic pregnancy diagnosis, and validation was performed using bootstrapping. Six of the 12 markers were differentially expressed between those with ectopic pregnancy and intrauterine pregnancy (P<.001) with fair diagnostic properties (area under the curve greater than 0.6) when examined individually (inhibin A, progesterone, activin A, vascular endothelial growth factor [VEGF], pregnancy-specific β-1-glycoprotein, and pregnancy-associated plasma protein-A). Six additional markers were found to have limited value. Using a two-step diagnostic algorithm with four markers (progesterone, VEGF, inhibin A, activin A), we diagnosed 42% of the sample with perfect specificity and 98% (93-100%) sensitivity. Overall, a single ectopic pregnancy was misclassified, achieving 99% (96-100%) accuracy. Evaluating a large number of biomarkers simultaneously demonstrates that most of the putative markers of ectopic pregnancy are not useful. However, a select few can distinguish ectopic pregnancy from intrauterine pregnancy with superior accuracy as part of a multiple marker test. : ClinicalTrials.gov, www.clinicaltrials.gov, NCT00194168.

Development of a Multiple Marker Test for Ectopic Pregnancy

Development of a Multiple Marker Test for Ectopic Pregnancy

Multiple marker test for the accurate diagnosis of ectopic pregnancy

OBJECTIVE: Many serum markers have been proposed to aid in the identification of an ectopic pregnancy (EP) but few have been validated. Most studies have been limited by sample size and design. The goal of this study was to assess putative markers to identify which can be used in combination to improve accuracy.

MTHFR and MSX1 contribute to the risk of nonsyndromic cleft lip/palate

Recent studies suggest that multiple interacting loci, with possible additional environmental factors, influence the risk for nonsyndromic oral clefts, one of the most common birth defects in humans. Advances in high-throughput genotyping technology allow the testing of multiple markers, simultaneously, in many candidate genes. We tested for associations between 176 haplotype-tagging single nucleotide polymorphisms (SNPs) in 18 candidate genes/loci and nonsyndromic clefts in a case-control study in an Estonian sample (153 patients, 205 controls). The most significant associations with nonsyndromic cleft lip with or without cleft palate (CL/P) were found for SNPs in MSX1, MTHFR, and PVRL2, including several common haplotypes in the MTHFR and MSX1 genes. The strongest association was observed for rs6446693 in the MSX1 region, which remained statistically significant after Bonferroni correction. The strongest association with nonsyndromic cleft palate (CP) was found for the SNP rs11624283 in the JAG2 gene. Epistatic interactions were observed for SNPs within PVRL2, between BCL3 and EDN1, and between IRF6 and MSX1 genes. This study provides further evidence implicating MSX1 and MTHFR in the etiology of nonsyndromic CL/P across different populations.

Sex‐specific association of the reelin gene with bipolar disorder

The Reelin gene (RELN) encodes a secretory glycoprotein critical for brain development and synaptic plasticity. Post-mortem studies have shown lower Reelin protein levels in the brains of patients with schizophrenia and bipolar disorder (BP) compared with controls. In a recent genome-wide association study of schizophrenia, the strongest association was found in a marker within RELN, although this association was seen only in women. In this study, we investigated whether genetic variation in RELN is associated with BP in a large family sample. We genotyped 75 tagSNPs and 6 coding SNPs in 1,188 individuals from 318 nuclear families, including 554 affected offspring. Quality control measures, transmission-disequilibrium tests (TDTs), and empirical simulations were performed in PLINK. We found a significant overtransmission of the C allele of rs362719 to BP offspring (OR = 1.47, P = 5.9 x 10(-4)); this withstood empirical correction for testing of multiple markers (empirical P = 0.048). In a hypothesis-driven secondary analysis, we found that the association with rs362719 was almost entirely accounted for by overtransmission of the putative risk allele to affected females (OR(Female) = 1.79, P = 8.9 x 10(-5) vs. OR(Male) = 1.12, P = 0.63). These results provide preliminary evidence that genetic variation in RELN is associated with susceptibility to BP and, in particular, to BP in females. However, our findings should be interpreted with caution until further replication and functional assays provide convergent support.

13: Development of a noninvasive test for intraamniotic infection using proteomic analysis of cervicovaginal fluid in women with preterm labor

ObjectiveTo develop a noninvasive test for intraamniotic infection (IAI) in women with preterm labor, intact membranes (PTL-I).Study DesignAmong 105 cases of PTL-I before 37 wks, IAI was defined by amniocentesis results: positive amniotic fluid culture and/or 16S ribosomal DNA PCR (16S-rDNA), a highly sensitive & specific test for presence of eubacteria, Mycoplasma, and Ureaplasma sp. Immunoassays were used to quantitate proteins in cervicovaginal fluid (CVF). Candidate CVF proteins were entered individually and in combination into logistic regression models.ResultsIAI was present in 13% (14/105), 11 by both 16S-rDNA & culture, 3 by 16S-rDNA alone. From 75 candidate CVF proteins associated with IAI, 5 were included in a final model: 1 plasma protein, 2 cytokine/chemokines, 1 cell adhesion protein, 1 peroxidase. Final model had area under ROC 0.983. A dichotomous classification rule based on these 5 proteins had sensitivity 93%, specificity 93%, PPV 72%, NPV 99% for prediction of IAI, and screen positive rate 19%. Test performance was not impaired by blood in the CVF specimen (present in 12 cases without IAI, none with IAI.)ConclusionIn PTL-I, the CVF proteome is measurably altered by IAI. A prototype multiple-marker test based on the concentrations of 5 distinct proteins in CVF appears to discriminate between IAI and non-infected cases, potentially reducing need for amniocentesis. Such a test could be very useful in the management of PTL-I. Research regarding the role of various proteins in CVF may yield insight into the pathophysiology of PTL. ObjectiveTo develop a noninvasive test for intraamniotic infection (IAI) in women with preterm labor, intact membranes (PTL-I). To develop a noninvasive test for intraamniotic infection (IAI) in women with preterm labor, intact membranes (PTL-I). Study DesignAmong 105 cases of PTL-I before 37 wks, IAI was defined by amniocentesis results: positive amniotic fluid culture and/or 16S ribosomal DNA PCR (16S-rDNA), a highly sensitive & specific test for presence of eubacteria, Mycoplasma, and Ureaplasma sp. Immunoassays were used to quantitate proteins in cervicovaginal fluid (CVF). Candidate CVF proteins were entered individually and in combination into logistic regression models. Among 105 cases of PTL-I before 37 wks, IAI was defined by amniocentesis results: positive amniotic fluid culture and/or 16S ribosomal DNA PCR (16S-rDNA), a highly sensitive & specific test for presence of eubacteria, Mycoplasma, and Ureaplasma sp. Immunoassays were used to quantitate proteins in cervicovaginal fluid (CVF). Candidate CVF proteins were entered individually and in combination into logistic regression models. ResultsIAI was present in 13% (14/105), 11 by both 16S-rDNA & culture, 3 by 16S-rDNA alone. From 75 candidate CVF proteins associated with IAI, 5 were included in a final model: 1 plasma protein, 2 cytokine/chemokines, 1 cell adhesion protein, 1 peroxidase. Final model had area under ROC 0.983. A dichotomous classification rule based on these 5 proteins had sensitivity 93%, specificity 93%, PPV 72%, NPV 99% for prediction of IAI, and screen positive rate 19%. Test performance was not impaired by blood in the CVF specimen (present in 12 cases without IAI, none with IAI.) IAI was present in 13% (14/105), 11 by both 16S-rDNA & culture, 3 by 16S-rDNA alone. From 75 candidate CVF proteins associated with IAI, 5 were included in a final model: 1 plasma protein, 2 cytokine/chemokines, 1 cell adhesion protein, 1 peroxidase. Final model had area under ROC 0.983. A dichotomous classification rule based on these 5 proteins had sensitivity 93%, specificity 93%, PPV 72%, NPV 99% for prediction of IAI, and screen positive rate 19%. Test performance was not impaired by blood in the CVF specimen (present in 12 cases without IAI, none with IAI.) ConclusionIn PTL-I, the CVF proteome is measurably altered by IAI. A prototype multiple-marker test based on the concentrations of 5 distinct proteins in CVF appears to discriminate between IAI and non-infected cases, potentially reducing need for amniocentesis. Such a test could be very useful in the management of PTL-I. Research regarding the role of various proteins in CVF may yield insight into the pathophysiology of PTL. In PTL-I, the CVF proteome is measurably altered by IAI. A prototype multiple-marker test based on the concentrations of 5 distinct proteins in CVF appears to discriminate between IAI and non-infected cases, potentially reducing need for amniocentesis. Such a test could be very useful in the management of PTL-I. Research regarding the role of various proteins in CVF may yield insight into the pathophysiology of PTL.

Association of SLC6A4 variants with obsessive-compulsive disorder in a large multicenter US family study

Genetic association studies of SLC6A4 (SERT) and OCD have been equivocal. We genotyped 1 241 persons in 278 pedigrees from the OCD Collaborative Genetics Study for 13 SNPs, the LPR indel with molecular haplotypes at rs25531, VNTR polymorphisms in introns 2 and 7, and a 381-bp deletion 3’ to the LPR. We analyzed using the Family Based Association Test (FBAT) under additive, dominant, recessive, and genotypic models, using both OCD and sex-stratified OCD as phenotype.Two-point FBAT analysis detected association with Int2 (p= 0.0089) and Int7 (p= 0.0187) (genotypic model). Sex-stratified 2-point analysis showed strong association in females with Int2 (p< 0.0002), significant after correction for LD, multiple marker- and model testing (pAdj= 0.0069). The SLC6A4 gene is composed of two haplotype blocks (our data and the HapMap); FBAT whole-marker analysis using this structure was not significant.Several noteworthy non-significant results emerged. We found no evidence for over-transmission of the LPR LA allele (GRR= 1.11, 95% CI: 0.77–1.60) (see Hu et al.1), however rare individual haplotypes containing LA with p<0.05 were observed. Similarly, 3 individuals (2 with OCD/OCPD) carried the rare I425V SLC6A4 variant- but none passed it on to their 6 OCD-affected offspring, suggesting it is unlikely solely responsible for the “OCD plus syndrome” (see Ozaki et al.2).In conclusion, we found evidence of genetic association at the SLC6A4 locus with OCD. Noteworthy lack of association at the LPR, LPR-rs25531, and rare 425V variants suggests hypotheses about OCD risk need revision to accommodate these new findings, including a possible gender effect.

Editor’s Choice

Editor’s Choice

Methods for Detecting Associations with Rare Variants for Common Diseases: Application to Analysis of Sequence Data

Although whole-genome association studies using tagSNPs are a powerful approach for detecting common variants, they are underpowered for detecting associations with rare variants. Recent studies have demonstrated that common diseases can be due to functional variants with a wide spectrum of allele frequencies, ranging from rare to common. An effective way to identify rare variants is through direct sequencing. The development of cost-effective sequencing technologies enables association studies to use sequence data from candidate genes and, in the future, from the entire genome. Although methods used for analysis of common variants are applicable to sequence data, their performance might not be optimal. In this study, it is shown that the collapsing method, which involves collapsing genotypes across variants and applying a univariate test, is powerful for analyzing rare variants, whereas multivariate analysis is robust against inclusion of noncausal variants. Both methods are superior to analyzing each variant individually with univariate tests. In order to unify the advantages of both collapsing and multiple-marker tests, we developed the Combined Multivariate and Collapsing (CMC) method and demonstrated that the CMC method is both powerful and robust. The CMC method can be applied to either candidate-gene or whole-genome sequence data.