A parametric approach to kinship hypothesis testing using identity-by-descent parameters

There is a large number of applications where family relationships need to be determined from DNA data. In forensic science, competing ideas are in general verbally formulated as the two hypotheses of a test. For the most common paternity case, the null hypothesis states that the alleged father is the true father against the alternative hypothesis that the father is an unrelated man. A likelihood ratio is calculated to summarize the evidence. We propose an alternative framework whereby a model and the hypotheses are formulated in terms of parameters representing identity-by-descent probabilities. There are several advantages to this approach. Firstly, the alternative hypothesis can be completely general. Specifically, the alternative does not need to specify an unrelated man. Secondly, the parametric formulation corresponds to the approach used in most other applications of statistical hypothesis testing and so there is a large theory of classical statistics that can be applied. Theoretical properties of the test statistic under the null hypothesis are studied. An extension to trios of individuals has been carried out. The methods are exemplified using simulations and a real dataset of 27 Spanish Romani individuals.

Gene variations in oestrogen pathways, CYP19A1, daily 17β-estradiol and mammographic density phenotypes in premenopausal women

INTRODUCTION

High mammographic density is an established breast cancer risk factor, and circulating oestrogen influences oestrogen-regulating gene expression in breast cancer development. However, less is known about the interrelationships of common variants in the CYP19A1 gene, daily levels of oestrogens, mammographic density phenotypes and body mass index (BMI) in premenopausal women.

METHODS

Based on plausible biological mechanisms related to the oestrogen pathway, we investigated the association of single nucleotide polymorphisms (SNPs) in CYP19A1, 17β-estradiol and mammographic density in 202 premenopausal women. DNA was genotyped using the Illumina Golden Gate platform. Daily salivary 17β-estradiol concentrations were measured throughout an entire menstrual cycle. Mammographic density phenotypes were assessed using a computer-assisted method (Madena). We determined associations using multivariable linear and logistic regression models.

RESULTS

The minor alleles of rs749292 were positively (P = 0.026), and the minor alleles of rs7172156 were inversely (P = 0.002) associated with daily 17β-estradiol. We observed an 87% lower level of daily 17β-estradiol throughout a menstrual cycle in heavier women (BMI >23.6 kg/m(2)) of rs7172156 with minor genotype aa compared with major genotype AA. Furthermore, the rs749292 minor alleles were inversely associated with absolute mammographic density (P = 0.032). Lean women with rs749292 minor alleles had 70 to 80% lower risk for high absolute mammographic density (>32.4 cm(2)); Aa: odds ratio (OR) = 0.23 (95% CI 0.07 to 0.75). Lean women with rs7172156 minor homozygous genotype had OR 5.45 for high absolute mammographic density (aa: OR = 5.45 (95% CI 1.13 to 26.3)).

CONCLUSION

Our findings suggest that two SNPs in CYP19A1, rs749292 and rs7172156, are associated with both daily oestrogen levels and mammographic density phenotypes. BMI may modify these associations, but larger studies are needed.

Familias 3 - Extensions and new functionality

In relationship testing the aim is to determine the most probable pedigree structure given genetic marker data for a set of persons. Disaster Victim Identification (DVI) based on DNA data from presumed relatives of the missing persons can be considered to be a collection of relationship problems. Forensic calculations in investigative mode address questions like "How many markers and reference persons are needed?" Such questions can be answered by simulations. Mutations, deviations from Hardy-Weinberg Equilibrium (or more generally, accounting for population substructure) and silent alleles cannot be ignored when evaluating forensic evidence in case work. With the advent of new markers, so called microvariants have become more common. Previous mutation models are no longer appropriate and a new model is proposed. This paper describes methods designed to deal with DVI problems and a new simulation model to study distribution of likelihoods. There are softwares available, addressing similar problems. However, for some problems including DVI, we are not aware of freely available validated software. The Familias software has long been widely used by forensic laboratories worldwide to compute likelihoods in relationship scenarios, though previous versions have lacked desired functionality, such as the above mentioned. The extensions as well as some other novel features have been implemented in the new version, freely available at www.familias.no. The implementation and validation are briefly mentioned leaving complete details to Supplementary sections.

Regression models for DNA-mixtures

This paper deals with the statistical interpretation of DNA mixture evidence. The conventional methods used in forensic casework today use something like 16 STR-markers. Power can be increased by rather using SNP-markers. New statistical methods are then needed, and we present a regression framework. The basic idea is that the traditional forensic hypotheses, commonly denoted HD and HP, are replaced by parametric versions: a person contributes to a mixture if and only if the fraction he contributes is greater than 0. This contributed fraction is a parameter of the regression model. The regression model uses the peak heights directly and there is no need to specify or estimate the number of contributors to the mixture. Also, drop-in and drop-out pose no principal problems. Data from 25 controlled blinded experiments were used to test the model. The number of contributors varied between 2 and 5, and the fractions contributed ranged from 0.01 to 0.99. The fractions were accurately estimated by the regression analyses. There were no false positives (i.e., in no cases were non-contributors declared to contributors). Some false negatives occurred for fractions of 0.1 or lower. Simulations were performed to test the model further. The analyses show that useful estimates can be obtained from a relatively small number of SNP-markers. Reasonable results are achieved using 300 markers which is close to the 313 SNPs in the controlled experiment. Increasing the number of SNPs, the analyses demonstrate that individuals contributing as little as 1% can reliably be detected, which suggests that cases beyond the reach of conventional forensic methods today can be reported.

Exact computation of the distribution of likelihood ratios with forensic applications

If complex DNA profiles, conditioned on multiple individuals are evaluated, it may be difficult to assess the strength of the evidence based on the likelihood ratio. A likelihood ratio does not give information about the relative weights that are provided by separate contributors. Alternatively, the observed likelihood ratio can be evaluated with respect to the distribution of the likelihood ratio under the defense hypothesis. We present an efficient algorithm to compute an exact distribution of likelihood ratios that can be applied to any LR-based model. The distribution may have several applications, but is used here to compute a p-value that corresponds to the observed likelihood ratio. The p-value is the probability that a profile under the defense hypothesis, substituted for a questioned contributor e.g. suspect, would attain a likelihood ratio which is at least the same magnitude as that observed. The p-value can be thought of as a scaled version of the likelihood ratio, giving a quantitative measure of the strength of the evidence relative to the specified hypotheses and the model used for the analysis. The algorithm is demonstrated on examples based on real data. R code for the algorithm is freely available in the R package euroMix.

Abstract 1362: Dyslipidemia, excess weight and high mammographic density are associated with high levels of daily estrogen and progesterone

Background: Dyslipidemia, excess weight, and high mammographic density have independently been associated with breast cancer development. However, little is known regarding the combined effect of dyslipidemia, excess weight and mammographic density on cyclic variation in estrogen and progesterone.

Material and Methods: 202 premenopausal women (25-35 years) participated in the Norwegian EBBA-I study including clinical examinations, and fasting blood sampling. Computer-assisted percent mammographic density (Madena) was obtained from digitized mammograms taken at day 7-12 of menstrual cycle. Daily saliva samples were collected across an entire menstrual cycle, and concentrations of 17β-estradiol and progesterone were measured at the Reproductive Ecology Laboratory, Harvard University, USA. Uni and multivariable linear and logistic regression models were used to study the combined association of high-density lipoprotein cholesterol (HDL-C), body mass index (BMI) and mammographic density with daily concentrations of 17β-estradiol and progesterone.

Results: Among women with mean age of 30.7 years, mean percent mammographic density 29.8 %, mean BMI 24.4 kg/m2, mean total cholesterol 4.45 mmol/l, and mean HDL-C 1.54 mmol/l, we observed overall mean salivary 17β-estradiol 16.2 pmol/l and progesterone 129.3 pmol/l. We used median split and women characterized by lower than median HDL-C (≤ 1.51 mmol/l), higher than median BMI (> 23.6 kg/m2), and higher than median percent mammographic density (> 28.5 %) (unfavorable profile), had higher concentrations of both 17β-estradiol (p = 0.005) and progesterone (p = 0.016) across the entire menstrual cycle, compared with women characterized by higher HDL-C(> 1.51 mmol/l), lower BMI (≤ 23.6 kg/m2) and lower percent mammographic density (≤ 28.5 %) (favorable profile). Comparing the profiles, women with an unfavorable profile had 46 % higher overall mean 17β-estradiol (17β-estradiol; 22.2 versus 15.9 pmol/l) and 48% higher overall mean progesterone (progesterone; 187.5 versus 126.1pmol/l). These factors also showed strong associations with differences in AUC (area under curve) of these sex steroid hormones across the entire menstrual cycle, reflecting cumulative exposure. Women characterized by unfavorable profile had 48 % higher AUC estradiol compared with women having favorable profile (AUCe, 387, 95 % confidence interval (CI) 244 - 531 versus 262, 95% CI 244 - 281). Furthermore, women with unfavorable profile had 47 % higher AUC progesterone than women with favorable profile (AUCp, 1929, 95 % CI 1125 - 2733 versus 1309, 95% CI 1211 -1408).

Conclusion: A combination of low HDL-C, excess weight, and high percent mammographic density, was strongly associated with higher daily levels of 17β-estradiol and progesterone, and could in part explain the association of these factors with increased risk of breast cancer development.

Citation Format: Vidar G. Flote, Hanne Frydenberg, Giske Ursin, Anita Iversen, Morten W. Fagerland, Peter T. Ellison, Erik A. Wist, Thore Egeland, Anne-Sofie Furberg, Inger Thune. Dyslipidemia, excess weight and high mammographic density are associated with high levels of daily estrogen and progesterone. . [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1362. doi:10.1158/1538-7445.AM2013-1362

Evaluating methods to correct for population stratification when estimating paternity indexes

The statistical interpretation of the forensic genetic evidence requires the use of allelic frequency estimates in the reference population for the studied markers. Differences in the genetic make up of the populations can be reflected in statistically different allelic frequency distributions. One can easily figure out that collecting such information for any given population is not always possible. Therefore, alternative approaches are needed in these cases in order to compensate for the lack of information. A number of statistics have been proposed to control for population stratification in paternity testing and forensic casework, Fst correction being the only one recommended by the forensic community. In this study we aimed to evaluate the performance of Fst to correct for population stratification in forensics. By way of simulations, we first tested the dependence of Fst on the relative sizes of the sub-populations, and second, we measured the effect of the Fst corrections on the Paternity Index (PI) values compared to the ones obtained when using the local reference database. The results provide clear-cut evidence that (i) Fst values are strongly dependent on the sampling scheme, and therefore, for most situations it would be almost impossible to estimate real values of Fst; and (ii) Fst corrections might unfairly correct PI values for stratification, suggesting the use of local databases whenever possible to estimate the frequencies of genetic profiles and PI values.

Using object oriented bayesian networks to model linkage, linkage disequilibrium and mutations between STR markers

In a number of applications there is a need to determine the most likely pedigree for a group of persons based on genetic markers. Adequate models are needed to reach this goal. The markers used to perform the statistical calculations can be linked and there may also be linkage disequilibrium (LD) in the population. The purpose of this paper is to present a graphical Bayesian Network framework to deal with such data. Potential LD is normally ignored and it is important to verify that the resulting calculations are not biased. Even if linkage does not influence results for regular paternity cases, it may have substantial impact on likelihood ratios involving other, more extended pedigrees. Models for LD influence likelihoods for all pedigrees to some degree and an initial estimate of the impact of ignoring LD and/or linkage is desirable, going beyond mere rules of thumb based on marker distance. Furthermore, we show how one can readily include a mutation model in the Bayesian Network; extending other programs or formulas to include such models may require considerable amounts of work and will in many case not be practical. As an example, we consider the two STR markers vWa and D12S391. We estimate probabilities for population haplotypes to account for LD using a method based on data from trios, while an estimate for the degree of linkage is taken from the literature. The results show that accounting for haplotype frequencies is unnecessary in most cases for this specific pair of markers. When doing calculations on regular paternity cases, the markers can be considered statistically independent. In more complex cases of disputed relatedness, for instance cases involving siblings or so-called deficient cases, or when small differences in the LR matter, independence should not be assumed. (The networks are freely available at http://arken.umb.no/~dakl/BayesianNetworks.).

Ultra-short course sirolimus contributes to effective GVHD prophylaxis after reduced-intensity allogeneic hematopoietic cell transplantation

Reduced-intensity conditioning (RIC) allo-SCT is a potentially curative treatment approach for patients with relapsed Hodgkin's or non-Hodgkin's lymphoma. In the present study, 37 patients underwent RIC allo-SCT after induction treatment with EPOCH-F(R) using a novel form of dual-agent immunosuppression for GVHD prophylaxis with CsA and sirolimus. With a median follow-up of 28 months among survivors, the probability for OS at 3 and 5 years was 56%. Treatment-related mortality was 16% at day +100 and 30% after 1 year of transplant. Acute GVHD grades II-IV developed in 38% of patients, suggesting that the regimen consisting of CsA and an ultra-short course of sirolimus is effective in the prevention of acute GVHD.

A mild form of Mucopolysaccharidosis IIIB diagnosed with targeted next-generation sequencing of linked genomic regions

Next-generation sequencing (NGS) techniques have already shown their potential in the identification of mutations underlying rare inherited disorders. We report here the application of linkage analysis in combination with targeted DNA capture and NGS to a Norwegian family affected by an undiagnosed mental retardation disorder with an autosomal recessive inheritance pattern. Linkage analysis identified two loci on chromosomes 9 and 17 which were subject to target enrichment by hybridization to a custom microarray. NGS achieved 20-fold or greater sequence coverage of 83% of all protein-coding exons in the target regions. This led to the identification of compound heterozygous mutations in NAGLU, compatible with the diagnosis of Mucopolysaccharidosis IIIB (MPS IIIB or Sanfilippo Syndrome type B). This diagnosis was confirmed by demonstrating elevated levels of heparan sulphate in urine and low activity of α-N-acetyl-glucosaminidase in cultured fibroblasts. Our findings describe a mild form of MPS IIIB and illustrate the diagnostic potential of targeted NGS in Mendelian disease with unknown aetiology.

Using X-chromosomal markers in relationship testing: calculation of likelihood ratios taking both linkage and linkage disequilibrium into account

X-chromosomal markers in forensic genetics have become more widely used during recent years, particularly for relationship testing. Linkage and linkage disequilibrium (LD) must typically be accounted for when using close X-chromosomal markers. Thus, when producing the weight-of-evidence, given by a DNA-analysis with markers that are linked, the normally used product rule is invalid. Here we present an implementation of an efficient model for calculating likelihood ratios (LRs) with markers on the X-chromosome which are linked and in LD. Furthermore, the model was applied on several cases based on data from the eight X-chromosomal loci included in the Mentype(®) Argus X-8 (Biotype). Using a simulation approach we showed that the use of X-chromosome data can offer valuable information for choosing between the alternatives in each of the cases we studied, and that the LR can be high in several cases. We demonstrated that when linkage and LD were disregarded, as opposed to taken into account, the difference in calculated LRs could be considerable. When these differences were large, the estimated haplotype frequencies often had a strong impact and we present a method to estimate haplotype frequencies. Our conclusion is that linkage and LD should be accounted for when using the tested set of markers, and the used model is an efficient way of doing so.

FTO genotype and weight gain in obese and normal weight adults from a Norwegian population based cohort (the HUNT study)

The fat mass and obesity associated gene ( FTO) is associated with bodyweight and obesity. The aim of this study was to investigate if FTO genotype affects weight gain in adulthood. We investigated the weight development over a period of 11 years in a case-control study, consisting of 1,632 cases (BMI≥35 kg/m (2)) and 3,379 normal weight controls (BMI 20-24.9 kg/m (2)) from a Norwegian population based cohort, the HUNT study. Subjects were aged 20-80 at baseline, 25% men and 75% women. FTO genotype was assessed by genotyping of the SNP rs1421085. A strong association between FTO and obesity was found, consistent with an additive gene effect. Cases had an average weight gain of 11.1 kg, whereas controls had an average weight gain of 1.4 kg. Genotype was neither associated with weight gain in obese, nor controls. Cases had an average weight gain of 10.7 kg for individuals with zero risk alleles, 11.3 for one risk allele and 11.1 kg for two risk alleles. Controls had an average weight gain of 1.4 kg, 1.4 and 1.3 for the respective genotypes. In conclusion, FTO was associated with obesity, but not with weight gain in adults during 11 years of follow-up.

Unrelated hematopoietic stem cell donors as research subjects

Requests for participation of unrelated stem cell donors in research transplant protocols are becoming more frequent. World Marrow Donor Association calls on donor registries to participate in research activities. Here, we discuss various implications of research participation and make some recommendations as how to make this possible.

X-linked congenital adrenal hypoplasia with hypogonadotropic hypogonadism caused by an inversion disrupting a conserved noncoding element upstream of the NR0B1 (DAX1) gene

CONTEXT

X-linked congenital adrenal hypoplasia with hypogonadotropic hypogonadism (AHCH) is known to be caused by coding mutations in the nuclear receptor subfamily 0, group B, member 1 (NR0B1) gene, encoding the transcriptional repressor dosage-sensitive sex-reversal adrenal hypoplasia critical region on the X chromosome protein 1 (DAX1).

OBJECTIVE/PATIENTS

Four males in a family were affected by AHCH. Our aim was to locate the genetic cause of their disease, knowing that they had no mutation in the obvious candidate gene, NR0B1.

DESIGN

Linkage analysis of the X chromosome and mutational screening of conserved noncoding regions upstream of NR0B1 were performed. To functionally characterize the genetic defect, studies of transcription and expression of DAX1 and steroidogenic factor 1 (SF-1) were done.

RESULTS

A 60 Mb inversion on the X chromosome with one of the inversion breakpoints located in a conserved noncoding region 4 kb upstream of NR0B1 was detected. The inversion causes relocation of a putative SF-1 binding site implicated in murine gonadal development. A reporter construct lacking this enhancer element upstream of NR0B1 was unresponsive to SF-1 transcriptional activation. Immunohistochemistry suggested that the inversion leads to SF-1 silencing in the patients' testes both in childhood and in adult life.

CONCLUSION

We report a noncoding mutation causing AHCH, an inversion resulting in a phenotype similar to what is caused by intragenic NR0B1 null mutations. The inversion seems to disrupt and/or relocate regulatory sites crucial in DAX1 expression.

A CLEC16A variant confers risk for juvenile idiopathic arthritis and anti-cyclic citrullinated peptide antibody negative rheumatoid arthritis

Objective

Variants in CLEC16A have conferred susceptibility to autoimmune diseases in genome-wide association studies. The present work aimed to investigate the locus' involvements in juvenile idiopathic arthritis (JIA) and further explore the association with rheumatoid arthritis (RA), type 1 diabetes (T1D) and Addison's disease (AD) in the Norwegian population.

Methods

Three single nucleotide polymorphisms (SNPs) were genotyped in patients with RA (n=809), JIA (n=509), T1D (n=1211) and AD (n=414) and in healthy controls (n=2149).

Results

All diseases were associated with CLEC16A, but with different SNPs. The intron 22 SNP, rs6498169, was associated with RA (p=0.006) and JIA (p=0.016) and the intron 19 SNPs, rs12708716/rs12917716, with T1D (p=1×10−5) and AD (p=2×10−4). The RA association was confined to the anti-cyclic citrullinated peptide antibody (anti-CCP) negative subgroup (p=2×10−4).

Conclusion

This is the first report of a CLEC16A association with JIA and a split of the RA association according to anti-CCP status. Different causative variants underlie the rheumatic versus the organ specific diseases.

Parental SCN1A mutation mosaicism in familial Dravet syndrome

Different SCN1A mutations are known to cause a variety of phenotypes, such as generalized epilepsy with febrile seizures plus (GEFS+), Dravet syndrome and familial hemiplegic migraine (FHM). In Dravet syndrome, most mutations are de novo and familial cases are rare. In this study, Dravet syndrome is observed in two maternal half sisters. They have healthy fathers and their common mother has never experienced seizures, but has a lifelong history of migraine. Direct sequencing of DNA extracted from blood revealed a heterozygous SCN1A nonsense mutation c.3985C>T in the sisters, but not in the mother. The mutation induces a premature stop codon and probably leads to a non-functional protein. Further examination of the mother's DNA showed that she has a mosaicism of the mutation. This report of parental SCN1A nonsense mutation mosaicism in familial Dravet syndrome suggests that mosaicism might be more common than previously suspected and emphasizes the importance of taking mosaicism into account in genetic counselling of Dravet syndrome and SCN1A mutations. Furthermore, whether the migraine of the mother could be influenced by her SCN1A mutation mosaicism is not known, but increased awareness of migraine in future studies of SCN1A related epilepsies could clarify this intriguing link between migraine and epilepsy.