Humans express at least seven alcohol dehydrogenase (ADH) isoforms that are encoded by ADH gene cluster (ADH7–ADH1C–ADH1B–ADH1A–ADH6–ADH4–ADH5) at chromosome 4. ADHs are key catabolic enzymes for retinol and ethanol. The functional ADH variants (mostly rare) have been implicated in alcoholism risk. In addition to catalyzing the oxidation of retinol and ethanol, ADHs may be involved in the metabolic pathways of several neurotransmitters that are implicated in the neurobiology of neuropsychiatric disorders. In the present study, we comprehensively examined the associations between common ADH variants [minor allele frequency (MAF) >0.05] and 11 neuropsychiatric and neurological disorders. A total of 50,063 subjects in 25 independent cohorts were analyzed. The entire ADH gene cluster was imputed across these 25 cohorts using the same reference panels. Association analyses were conducted, adjusting for multiple comparisons. We found 28 and 15 single nucleotide polymorphisms (SNPs), respectively, that were significantly associated with schizophrenia in African-Americans and autism in European-Americans after correction by false discovery rate (FDR) (q <0.05); and 19 and 6 SNPs, respectively, that were significantly associated with these two disorders after region-wide correction by SNPSpD (8.9 × 10−5 ≤ p ≤ 0.0003 and 2.4 × 10−5 ≤ p ≤ 0.0003, respectively). No variants were significantly associated with the other nine neuropsychiatric disorders, including alcohol dependence. We concluded that common ADH variants conferred risk for both schizophrenia in African-Americans and autism in European-Americans.
Let Y1, …, Yn be a sequence whose underlying mean is a step function with an unknown number of the steps and unknown change points. The detection of the change points, namely the positions where the mean changes, is an important problem in such fields as engineering, economics, climatology and bioscience. This problem has attracted a lot of attention in statistics, and a variety of solutions have been proposed and implemented. However, there is scant literature on the theoretical properties of those algorithms. Here, we investigate a recently developed algorithm called the Screening and Ranking Algorithm (SaRa). We characterize the theoretical properties of SaRa and show its superiority over other commonly used algorithms. In particular, we develop a false discovery rate approach to the multiple change-point problem and show a strong sure coverage property for the SaRa.
Change-point detection; copy number variation; false discovery rate; high dimensional data; screening and ranking algorithm
Intraventricular hemorrhage (IVH) of the preterm neonate is a complex developmental disorder, with contributions from both the environment and the genome. IVH, or hemorrhage into the germinal matrix of the developing brain with secondary periventricular infarction, occurs in that critical period of time before the 32nd – 33rd week post-conception and has been attributed to changes in cerebral blood flow to the immature germinal matrix microvasculature. Emerging data suggest that genes subserving coagulation, inflammatory and vascular pathways, and their interactions with environmental triggers may influence both the incidence and severity of cerebral injury and are the subject of this review.
Polymorphisms in the Factor V Leiden gene are associated with the atypical timing of IVH suggesting an as yet unknown environmental trigger. The methylenetetra-hydrofolate reeducates (MTHFR) variants render neonates more vulnerable to cerebral injury in the presence of perinatal hypoxia. The present study demonstrates that the MTHFR 677C>T polymorphism and low 5 minute Apgar score additively increase the risk of IVH. Finally, review of published preclinical data suggests the stressors of delivery result in hemorrhage in the presence of mutations in collagen 4A1 (COL4A1), a major structural protein of the developing cerebral vasculature. Maternal genetics and fetal environment may also play a role.
Economically, Leuconostoc lactis is one of the most important species in the genus Leuconostoc. It plays an important role in the food industry including the production of dextrans and bacteriocins. Currently, traditional molecular typing approaches for characterisation of this species at the isolate level are either unavailable or are not sufficiently reliable for practical use. Multilocus sequence typing (MLST) is a robust and reliable method for characterising bacterial and fungal species at the molecular level. In this study, a novel MLST protocol was developed for 50 L. lactis isolates from Mongolia and China.
Sequences from eight targeted genes (groEL, carB, recA, pheS, murC, pyrG, rpoB and uvrC) were obtained. Sequence analysis indicated 20 different sequence types (STs), with 13 of them being represented by a single isolate. Phylogenetic analysis based on the sequences of eight MLST loci indicated that the isolates belonged to two major groups, A (34 isolates) and B (16 isolates). Linkage disequilibrium analyses indicated that recombination occurred at a low frequency in L. lactis, indicating a clonal population structure. Split-decomposition analysis indicated that intraspecies recombination played a role in generating genotypic diversity amongst isolates.
Our results indicated that MLST is a valuable tool for typing L. lactis isolates that can be used for further monitoring of evolutionary changes and population genetics.
Historically, the Mongol Empire ranks among the world's largest contiguous empires, and the Mongolians developed their unique lifestyle and diet over thousands of years. In this study, the intestinal microbiota of Mongolians residing in Ulan Bator, TUW province and the Khentii pasturing area were studied using 454 pyrosequencing and q-PCR technology. We explored the impacts of lifestyle and seasonal dietary changes on the Mongolians' gut microbes. At the phylum level, the Mongolians's gut populations were marked by a dominance of Bacteroidetes (55.56%) and a low Firmicutes to Bacteroidetes ratio (0.71). Analysis based on the operational taxonomic unit (OTU) level revealed that the Mongolian core intestinal microbiota comprised the genera Prevotella, Bacteroides, Faecalibacterium, Ruminococcus, Subdoligranulum and Coprococcus. Urbanisation and life-style may have modified the compositions of the gut microbiota of Mongolians from Ulan Bator, TUW and Khentii. Based on a food frequency questionnaire, we found that the dietary structure was diverse and stable throughout the year in Ulan Bator and TUW, but was simple and varied during the year in Khentii. Accordingly, seasonal effects on intestinal microbiota were more distinct in Khentii residents than in TUW or Ulan Bator residents.
To estimate whether progestin-induced endometrial shedding, prior to ovulation induction with clomiphene citrate, metformin, or a combination of both, affects ovulation, conception, and live birth rates in women with polycystic ovary syndrome (PCOS).
A secondary analysis of the data from 626 women with PCOS from the National Institutes of Child Health and Human Development Cooperative Reproductive Medicine Network trial was performed. Women had been randomized to up to six cycles of clomiphene citrate alone, metformin alone, or clomiphene citrate plus metformin. Women were assessed for occurrence of ovulation, conception, and live birth in relation to prior bleeding episodes (after either ovulation or exogenous progestin-induced withdrawal bleed).
While ovulation rates were higher in cycles preceded by spontaneous endometrial shedding than after anovulatory cycles (with or without prior progestin withdrawal), both conception and live birth rates were significantly higher after anovulatory cycles without progestin-induced withdrawal bleeding (live birth per cycle: spontaneous menses 2.2%; anovulatory with progestin withdrawal 1.6%; anovulatory without progestin withdrawal 5.3%; p<0.001). The difference was more marked when rate was calculated per ovulation (live birth per ovulation: spontaneous menses 3.0%; anovulatory with progestin withdrawal 5.4%; anovulatory without progestin withdrawal 19.7%; p < .001).
Conception and live birth rates are lower in women with PCOS after a spontaneous menses or progestin-induced withdrawal bleeding as compared to anovulatory cycles without progestin withdrawal. The common clinical practice of inducing endometrial shedding with progestin prior to ovarian stimulation may have an adverse effect on rates of conception and live birth in anovulatory women with PCOS.
Polycystic ovary syndrome (PCOS) patients are at increased risk of pregnancy complications, which may impair pregnancy outcome. Transfer of fresh embryos after superovulation may lead to abnormal implantation and placentation and further increase risk for pregnancy loss and complications. Some preliminary data suggest that elective embryo cryopreservation followed by frozen–thawed embryo transfer into a hormonally primed endometrium could result in a higher clinical pregnancy rate than that achieved by fresh embryo transfer.
This study is a multicenter, prospective, randomized controlled clinical trial (1:1 treatment ratio of fresh vs. elective frozen embryo transfers).. A total of 1,180 infertile PCOS patients undergoing the first cycle of in vitro fertilization (IVF) or intracytoplasmic sperm injection will be enrolled and randomized into two parallel groups. Participants in group A will undergo fresh embryo transfer on day 3 after oocyte retrieval, and participants in group B will undergo elective embryo cryopreservation after oocyte retrieval and frozen–thawed embryo transfer in programmed cycles. The primary outcome is the live birth rate. Our study is powered at 80 to detect an absolute difference of 10 at the significance level of 0.01 based on a two-sided test.
We hypothesize that elective embryo cryopreservation and frozen–thawed embryo transfer will reduce the incidence of pregnancy complications and increase the live birth rate in PCOS patients who need IVF to achieve pregnancy.
ClinicalTrials.gov Identifier: NCT01841528
Frozen–thawed embryo transfer; In vitro fertilization; Live birth; Polycystic ovarian syndrome
We aimed to identify novel, functional, replicable and genome-wide
significant risk regions specific for alcohol dependence using genome-wide
association studies (GWASs).
A discovery sample (1,409 European-American cases with alcohol
dependence and 1,518 European-American controls) and a replication sample
(6,438 European-Australian family subjects with 1,645 alcohol dependent
probands) underwent association analysis. Nineteen other cohorts with 11
different neuropsychiatric disorders served as contrast groups. Additional
eight samples underwent expression quantitative locus (eQTL) analysis.
A genome-wide significant risk gene region
(NKAIN1-SERINC2) was identified in a meta-analysis of
the discovery and replication samples. This region was enriched with 74 risk
SNPs (unimputed); half of them had significant cis-acting
regulatory effects. The distributions of -log(p) values for the SNP-disease
associations or SNP-expression associations in this region were consistent
throughout eight independent samples. Furthermore, imputing across the
NKAIN1-SERINC2 region, we found that among all 795 SNPs
in the discovery sample, 471 SNPs were nominally associated with alcohol
dependence (1.7×10−7≤p≤0.047); 53
survived region- and cohort-wide correction for multiple testing; 92 SNPs
were replicated in the replication sample (0.002≤p≤0.050).
This region was neither significantly associated with alcohol dependence in
African-Americans, nor with other non-alcoholism diseases. Finally,
transcript expression of genes in NKAIN1-SERINC2 was
significantly (p<3.4×10−7) associated
with expression of numerous genes in the neurotransmitter systems or
metabolic pathways previously associated with alcohol dependence.
NKAIN1-SERINC2 may harbor a causal variant(s) for
alcohol dependence. It may contribute to the disease risk by way of
neurotransmitter systems or metabolic pathways.
GWAS; genome-wide association studies; alcohol dependence; eQTL; risk region; replication
Alcohol and nicotine co-dependence can be considered as a more severe subtype of alcohol dependence. A portion of its risk may be attributable to genetic factors.
We searched for significant risk genomic regions specific for this disorder using a genome-wide association study (GWAS). A total of 8,847 subjects underwent gene-disease association analysis, including (i) a discovery cohort of 818 European-American cases with alcohol and nicotine co-dependence and 1,396 European-American controls, (ii) a replication cohort of 5,704 Australian family subjects with 907 affected offspring, and (iii) a replication cohort of 449 African-American cases and 480 African-American controls. Additionally, a total of 38,714 subjects of European or African descent in 18 independent cohorts with 10 other non-alcoholism neuropsychiatric disorders were analyzed as contrast. Furthermore, 90 unrelated HapMap CEU individuals, 93 European brain tissue samples and 80 European peripheral blood mononuclear cell (PBMC) samples underwent cis-acting expression quantitative locus (cis-eQTL) analysis.
We identified a significant risk region for alcohol and nicotine co-dependence between IPO11 and HTR1A on chromosome 5q that was reported to be suggestively associated with alcohol dependence previously. In the European-American discovery cohort, 381 SNPs in this region were nominally associated with alcohol and nicotine co-dependence (p<0.05); 57 associations of them survived region- and cohort-wide correction (α=3.6×10−6); and the top SNP (rs7445832) was significantly associated with alcohol and nicotine co-dependence at the genome-wide significance level (p=6.2×10−9). Furthermore, associations for 34 and 11 SNPs were replicated in the Australian and African-American replication cohorts, respectively. Among these replicable associations, 4 reached genome-wide significance level in the meta-analysis of European-Americans and European-Australians: rs7445832 (p=9.6×10−10), rs13361996 (p=8.2×10−9), rs62380518 (p=2.3×10−8) and rs7714850 (p=3.4×10−8). Cis-eQTL analysis showed that many risk SNPs in this region had nominally significant cis-acting regulatory effects on HTR1A or IPO11 mRNA expression. Finally, no markers were significantly associated with any other neuropsychiatric disorder examined.
We speculate that this IPO11-HTR1A region might harbor a causal variant for alcohol and nicotine co-dependence.
GWAS; alcohol and nicotine co-dependence; cis-eQTL; IPO11; HTR1A
The human gut microbiota consists of complex microbial communities, which possibly play crucial roles in physiological functioning and health maintenance. China has evolved into a multicultural society consisting of the major ethnic group, Han, and 55 official ethnic minority groups. Nowadays, these minority groups inhabit in different Chinese provinces and some of them still keep their unique culture and lifestyle. Currently, only limited data are available on the gut microbiota of these Chinese ethnic groups. In this study, 10 major fecal bacterial groups of 314 healthy individuals from 7 Chinese ethnic origins were enumerated by quantitative polymerase chain reaction. Our data confirmed that the selected bacterial groups were common to all 7 surveyed ethnicities, but the amount of the individual bacterial groups varied to different degree. By principal component and canonical variate analyses of the 314 individuals or the 91 Han subjects, no distinct group clustering pattern was observed. Nevertheless, weak differences were noted between the Han and Zhuang from other ethnic minority groups, and between the Heilongjiang Hans from those of the other provinces. Thus, our results suggest that the ethnic origin may contribute to shaping the human gut microbiota.
To investigate whether prenatal exposure to nicotine has an impact on several reading skill outcomes in school age children.
Using a longitudinal sample of 5,119 school age children in the Avon Longitudinal Study of Parents and Children (ALSPAC), 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 three categories: high (>17mg per day), low (≤17mg per day) and no exposure.
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 ALSPAC.
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.
Reading performance; reading skills; prenatal exposure to nicotine; ALSPAC
To determine whether self-reported menopausal symptoms are associated with measures of subclinical atherosclerosis.
Multi-center, randomized controlled trial.
Recently menopausal women (n=868) screened for the Kronos Early Estrogen Prevention Study (KEEPS).
Cross sectional analysis.
Main Outcome Measures
Baseline menopausal symptoms (hot flashes, dyspareunia, vaginal dryness, night sweats, palpitations, mood swings, depression, insomnia, irritability), serum estradiol (E2) levels and measures of atherosclerosis were assessed. Atherosclerosis was quantified using Coronary Artery Calcium (CAC) Agatston scores (n=771) and Carotid Intima-Media Thickness (CIMT). Logistic regression model of menopausal symptoms and E2 was used to predict CAC. Linear regression model of menopausal symptoms and E2 was used to predict CIMT. Correlation between length of time in menopause with menopausal symptoms, estradiol (E2), CAC, and CIMT were assessed.
In early menopausal women screened for KEEPS, neither E2 nor climacteric symptoms predicted the extent of subclinical atherosclerosis. Palpitations (p=0.09) and depression (p=0.07) approached significance as predictors of CAC. Other symptoms of insomnia, irritability, dyspareunia, hot flashes, mood swings, night sweats, and vaginal dryness were not associated with CAC. Women with significantly elevated CAC scores were excluded from further participation in KEEPS; in women meeting inclusion criteria, neither baseline menopausal symptoms nor E2 predicted CIMT. Years since menopause onset correlated with CIMT, dyspareunia, vaginal dryness and E2.
Self-reported symptoms in recently menopausal women are not strong predictors of subclinical atherosclerosis. Continued follow-up of this population will be performed to determine if baseline or persistent symptoms in the early menopause are associated with progression of cardiovascular disease.
KEEPS; estrogen; cardiovascular; menopause; CAC; CIMT; palpitations; depression
Robust variable selection procedures through penalized regression have been gaining increased attention in the literature. They can be used to perform variable selection and are expected to yield robust estimates. However, to the best of our knowledge, the robustness of those penalized regression procedures has not been well characterized. In this paper, we propose a class of penalized robust regression estimators based on exponential squared loss. The motivation for this new procedure is that it enables us to characterize its robustness that has not been done for the existing procedures, while its performance is near optimal and superior to some recently developed methods. Specifically, under defined regularity conditions, our estimators are n-consistent and possess the oracle property. Importantly, we show that our estimators can achieve the highest asymptotic breakdown point of 1/2 and that their influence functions are bounded with respect to the outliers in either the response or the covariate domain. We performed simulation studies to compare our proposed method with some recent methods, using the oracle method as the benchmark. We consider common sources of influential points. Our simulation studies reveal that our proposed method performs similarly to the oracle method in terms of the model error and the positive selection rate even in the presence of influential points. In contrast, other existing procedures have a much lower non-causal selection rate. Furthermore, we re-analyze the Boston Housing Price Dataset and the Plasma Beta-Carotene Level Dataset that are commonly used examples for regression diagnostics of influential points. Our analysis unravels the discrepancies of using our robust method versus the other penalized regression method, underscoring the importance of developing and applying robust penalized regression methods.
Robust regression; Variable selection; Breakdown point; Influence function
Twin and family studies establish the foundation for studying the genetic, environmental and cultural transmission effects for phenotypes. In this work, we make use of the well established statistical methods and theory for mixed models to assess cultural transmission in twin and family studies. Specifically, we address two critical yet poorly understood issues: the model identifiability in assessing cultural transmission for twin and family data and the biases in the estimates when sub-models are used. We apply our models and theory to two real data sets. A simulation is conducted to verify the bias in the estimates of genetic effects when the working model is a sub-model.
Twin and family study; Biometrical Genetic model; Cultural transmission; Biometrical Genetic model; Identifiability; Likelihood ratio test; Mixed-effects model
Increasing evidence suggests that rare and generally deleterious genetic variants might have strong impact on disease risks of not only Mendelian disease, but also many common diseases. However, identifying such rare variants remains to be challenging, and novel statistical methods and bioinformatic software must be developed. Hence, we have to extensively evaluate various methods under reasonable genetic models. While there are abundant genomic data, they are not most helpful for the evaluation of the methods because the disease mechanism is unknown. Thus, it is imperative that we simulate genomic data that mimic the real data containing rare variants and that enable us to impose a known disease penetrance model. Although resampling simulation methods have shown their advantages in computational efficiency and in preserving important properties such as linkage disequilibrium (LD) and allele frequency, they still have limitations as we demonstrated. We propose an algorithm that combines a regression-based imputation with resampling to simulate genetic data with both rare and common variants. Logistic regression model was employed to fit the relationship between a rare variant and its nearby common variants in the 1000 Genomes Project data and then applied to the real data to fill in one rare variant at a time using the fitted logistic model based on common variants. Individuals then were simulated using the real data with imputed rare variants. We compared our method with existing simulators and demonstrated that our method performed well in retaining the real sample properties, such as LD and minor allele frequency, qualitatively.
resampling; logistic regression; simulation; rare SNPs
Preterm (PT) subjects are at risk for developmental delay, and task-based studies suggest that developmental disorders may be due to alterations in neural connectivity. Since emerging data imply the importance of right cerebellar function for language acquisition in typical development, we hypothesized that PT subjects would have alternate areas of cerebellar connectivity, and that these areas would be responsible for differences in cognitive outcomes between PT subjects and term controls at age 20 years.
Nineteen PT and 19 term control young adults were prospectively studied using resting-state functional MRI (fMRI) to create voxel-based contrast maps reflecting the functional connectivity of each tissue element in the grey matter through analysis of the intrinsic connectivity contrast degree (ICC-d). Left cerebellar ICC-d differences between subjects identified a region of interest that was used for subsequent seed-based connectivity analyses. Subjects underwent standardized language testing, and correlations with cognitive outcomes were assessed.
There were no differences in gender, hand preference, maternal education, age at study, or Peabody Picture Vocabulary Test (PPVT) scores. Functional connectivity (FcMRI) demonstrated increased tissue connectivity in the biventer, simple and quadrangular lobules of the L cerebellum (p<0.05) in PTs compared to term controls; seed-based analyses from these regions demonstrated alterations in connectivity from L cerebellum to both R and L inferior frontal gyri (IFG) in PTs compared to term controls. For PTs but not term controls, there were significant positive correlations between these connections and PPVT scores (R IFG: r=0.555, p=0.01; L IFG: r=0.454, p=0.05), as well as Verbal Comprehension Index (VCI) scores (R IFG: r=0.472, p=0.04).
These data suggest the presence of a left cerebellar language circuit in PT subjects at young adulthood. These findings may represent either a delay in maturation or the engagement of alternative neural pathways for language in the developing PT brain.
Preterm; cerebellum; language systems; functional MRI; resting state intrinsic connectivity contrast degree
Aims: Some of the well-known functional alcohol dehydrogenase (ADH) gene variants (e.g. ADH1B*2, ADH1B*3 and ADH1C*2) that significantly affect the risk of alcohol dependence are rare variants in most populations. In the present study, we comprehensively examined the associations between rare ADH variants [minor allele frequency (MAF) <0.05] and alcohol dependence, with several other neuropsychiatric and neurological disorders as reference. Methods: A total of 49,358 subjects in 22 independent cohorts with 11 different neuropsychiatric and neurological disorders were analyzed, including 3 cohorts with alcohol dependence. The entire ADH gene cluster (ADH7–ADH1C–ADH1B–ADH1A–ADH6–ADH4–ADH5 at Chr4) was imputed in all samples using the same reference panels that included whole-genome sequencing data. We stringently cleaned the phenotype and genotype data to obtain a total of 870 single nucleotide polymorphisms with 0< MAF <0.05 for association analysis. Results: We found that a rare variant constellation across the entire ADH gene cluster was significantly associated with alcohol dependence in European-Americans (Fp1: simulated global P = 0.045), European-Australians (Fp5: global P = 0.027; collapsing: P = 0.038) and African-Americans (Fp5: global P = 0.050; collapsing: P = 0.038), but not with any other neuropsychiatric disease. Association signals in this region came principally from ADH6, ADH7, ADH1B and ADH1C. In particular, a rare ADH6 variant constellation showed a replicable association with alcohol dependence across these three independent cohorts. No individual rare variants were statistically significantly associated with any disease examined after group- and region-wide correction for multiple comparisons. Conclusion: We conclude that rare ADH variants are specific for alcohol dependence. The ADH gene cluster may harbor a causal variant(s) for alcohol dependence.
Genome-wide association studies (GWASs) at gene level are commonly used to understand biological mechanisms underlying complex diseases. In general, one response or outcome is used to present a disease of interest in such studies. In this study, we consider a multiple traits association test from gene level. We propose and examine a class of test statistics that summarizes the association information between single nucleotide polymorphisms (SNPs) and each of the traits. Our simulation studies demonstrate the advantage of gene-based multiple traits association tests when multiple traits share common genes. Using our proposed tests, we re-analyze the dataset from the Study of Addiction: Genetics and Environment (SAGE). Our result validates previous findings while presenting stronger evidence for consideration of multiple traits.
substance dependence; multiple traits; gene-based association test; generalized Kendall's tau
Large randomized clinical trials are becoming more costly, and resources to support them increasingly scarce. Biologic materials, such as blood, DNA, body fluids, or tissue samples collected and stored as a component of these studies represent an invaluable resource, to answer immediate secondary hypotheses, but also as archived material, linked to the study data, for the use of investigators long into the future. The regulatory climate surrounding the storage and future unconstrained utilization of biologic materials is evolving quickly. It is no longer acceptable simply to store samples and use them in an unbridled and unregulated fashion. Thus, to fully utilize the tremendous potential of biologic samples generated from large clinical trials and their related databases, investigators should consider proactively creating a biologic specimen repository, or biorepository. A repository likely assures appropriate subject consent, sample provenance, secure storage, and codified procedures for sample and data retrieval and sharing that protect the subject’s confidentiality, the investigator’s need for accurate data, and the limited resource. Importantly, the biorepository specimens/samples are typically collected in addition to local and core specimens obtained for the parent study that provide baseline assessments for safety and efficacy outcomes.
Biorepository; Repository; Reproductive Medicine Network
Neuroimaging data collected at repeated occasions are gaining increasing attention in the neuroimaging community due to their potential in answering questions regarding brain development, aging, and neurodegeneration. These datasets are large and complicated, characterized by the intricate spatial dependence structure of each response image, multiple response images per subject, and covariates that may vary with time. We propose a multiscale adaptive generalized method of moments (MA-GMM) approach to estimate marginal regression models for imaging datasets that contain time-varying, spatially-related responses and some time-varying covariates. Our method categorizes covariates into types to determine the valid moment conditions to combine during estimation. Further, instead of assuming independence of voxels (the components that make up each subject’s response image at each time point) as many current neuroimaging analysis techniques do, this method “adaptively smoothes” neuroimaging response data, computing parameter estimates by iteratively building spheres around each voxel and combining observations within the spheres with weights. MA-GMM’s development adds to the few available modeling approaches intended for longitudinal imaging data analysis. Simulation studies and an analysis of a real longitudinal imaging dataset from the Alzheimer’s Disease Neuroimaging Initiative are used to assess the performance of MA-GMM.
Generalized method of moments (GMM); Longitudinal neuroimaging data; Marginal modeling; Multiscale adaptive regression model (MARM); Smoothing; Time-varying covariates; Voxel-wise method
DNA Copy number variation (CNV) has recently gained considerable interest as a source of genetic variation that likely influences phenotypic differences. Many statistical and computational methods have been proposed and applied to detect CNVs based on data that generated by genome analysis platforms. However, most algorithms are computationally intensive with complexity at least O(n2), where n is the number of probes in the experiments. Moreover, the theoretical properties of those existing methods are not well understood. A faster and better characterized algorithm is desirable for the ultra high throughput data. In this study, we propose the Screening and Ranking algorithm (SaRa) which can detect CNVs fast and accurately with complexity down to O(n). In addition, we characterize theoretical properties and present numerical analysis for our algorithm.
Change-point detection; copy number variations; high dimensional data; screening and ranking algorithm
Acupuncture is an alternative therapy to induce ovulation in women with polycystic ovary syndrome (PCOS), but there is no study reporting the live birth rate following ovulation induction by acupuncture or its potential as an adjuvant treatment to clomiphene citrate (CC). We assess the efficacy of acupuncture with or without CC in achieving live births among 1000 PCOS women in Mainland China. This paper reports the methodology of an ongoing multicenter randomized controlled trial. The randomization scheme is coordinated through the central mechanism and stratified by the participating sites. Participants will be randomized into one of the four treatment arms: (A) true acupuncture and CC, (B) control acupuncture and CC, (C) true acupuncture and placebo CC, and (D) control acupuncture and placebo CC. To ensure the quality and integrity of the trial we have developed a unique multinational team of investigators and Data and Safety Monitoring Board. Up to the end of April 2013, 326 subjects were recruited. In conclusion, the success of this trial will allow us to evaluate the additional benefit of acupuncture beyond the first line medicine for fertility treatment in PCOS women in an unbiased manner.
Infertility afflicts fifteen percent of couples who wish to conceive. Despite intensive evaluation of both male and female partners, the etiology may remain unknown leading to a diagnosis of unexplained infertility. For such couples, treatment often entails ovulation induction (OI) with fertility medications coupled with intrauterine insemination. Complications of this therapy include ovarian hyperstimulation syndrome and creation of multiple gestation pregnancies, which can be complicated by preterm labor and delivery, and the associated neonatal morbidity and expense of care for preterm infants. The Assessment of Multiple Intrauterine Gestations from Ovarian Stimulation (AMIGOS) study is designed to assess whether OI in couples with unexplained infertility with an aromatase inhibitor produces mono-follicular development in most cycles, thereby reducing multiple gestations while maintaining a comparable pregnancy success rate to that achieved by OI with either gonadotropins or clomiphene citrate. These results will provide future guidance of therapy for couples with unexplained infertility, and if comparable pregnancy rates are achieved with a substantial reduction in multiple gestations, the public health benefit will be considerable.
Multiple gestation; ovulation induction; gonadotropins; aromatase inhibitor; unexplained infertility
Many women with polycystic ovary syndrome (PCOS) experience infertility and hirsutism and often seek treatment for both concurrently. We investigated whether women who ovulate in response to treatment with clomiphene citrate), metformin, or both would have greater improvement in hirsutism compared to those who did not ovulate.
This is a secondary analysis evaluating the change in Ferriman-Gallwey score for the hirsute women (n = 505, 80.7%) from the Pregnancy in Polycystic Ovary Syndrome 1 study. This was a prospective, randomized, doubled-blind trial of 626 women with PCOS and infertility recruited from 12 university sites. They were treated with clomiphene citrate, metformin, or both (combination) for up to six cycles, and hirsutism evaluators were blinded to group assignment.
There was a significant decrease in the Ferriman-Gallwey score between baseline and completion of the study in each of the three individual groups (clomiphene citrate, p=0.024; metformin, p=0.005; combination, p<0.001). There was no significant difference in the degree to which the hirsutism score changed when comparing the three groups (p=0.44). The change in hirsutism was not associated with the duration of treatment or with the presence or absence of ovulation.
In infertile hirsute women with PCOS, treatment with clomiphene citrate, metformin, or both for up to 6 cycles does not alter hirsutism.
Clinical Trial Registration
ClinicalTrials.gov, www.clinicaltrials.gov, NCT00068861.
The present study searched for replicable risk genomic regions for alcohol and nicotine co-dependence using a genome-wide association strategy. The data contained a total of 3,143 subjects including 818 European-American (EA) cases with alcohol and nicotine co-dependence, 1,396 EA controls, 449 African-American (AA) cases and 480 AA controls. We performed separate genome-wide association analyses in EAs and AAs and a meta-analysis to derive combined p values, and calculated the genome-wide false discovery rate (FDR) for each SNP. Regions with p<5×10-7 together with FDR<0.05 in the meta-analysis were examined to detect all replicable risk SNPs across EAs, AAs and meta-analysis. These SNPs were followed with a series of functional expression quantitative trait locus (eQTL) analyses. We found a unique genome-wide significant gene region – SH3BP5-NR2C2 – that was enriched with 11 replicable risk SNPs for alcohol and nicotine co-dependence. The distributions of -log(p) values for all SNP-disease associations within this region were consistent across EAs, AAs, and meta-analysis (0.315≤r≤0.868; 8.1×10-52≤p≤3.6×10-5). In the meta-analysis, this region was the only association peak throughout chromosome 3 at p<0.0001. All replicable risk markers available for eQTL analysis had nominal cis- and trans-acting regulatory effects on gene expression. The transcript expression of the genes in this region was regulated partly by several nicotine dependence-related genes and significantly correlated with transcript expression of many alcohol and nicotine dependence-related genes. We concluded that the SH3BP5-NR2C2 region on Chromosome 3 might harbor causal loci for alcohol and nicotine co-dependence.
GWAS; alcohol and nicotine co-dependence