Modeling of African population history using f-statistics is biased when applying all previously proposed SNP ascertainment schemes.

f-statistics have emerged as a first line of analysis for making inferences about demographic history from genome-wide data. Not only are they guaranteed to allow robust tests of the fits of proposed models of population history to data when analyzing full genome sequencing data-that is, all single nucleotide polymorphisms (SNPs) in the individuals being analyzed-but they are also guaranteed to allow robust tests of models for SNPs ascertained as polymorphic in a population that is an outgroup in a phylogenetic sense to all groups being analyzed. True "outgroup ascertainment" is in practice impossible in humans because our species has arisen from a substructured ancestral population that does not descend from a homogeneous ancestral population going back many hundreds of thousands of years into the past. However, initial studies suggested that non-outgroup-ascertainment schemes might produce robust enough results using f-statistics, and that motivated widespread fitting of models to data using non-outgroup-ascertained SNP panels such as the "Affymetrix Human Origins array" which has been genotyped on thousands of modern individuals from hundreds of populations, or the "1240k" in-solution enrichment reagent which has been the source of about 70% of published genome-wide data for ancient humans. In this study, we show that while analyses of population history using such panels work well for studies of relationships among non-African populations and one African outgroup, when co-modeling more than one sub-Saharan African and/or archaic human groups (Neanderthals and Denisovans), fitting of f-statistics to such SNP sets is expected to frequently lead to false rejection of true demographic histories, and failure to reject incorrect models. Analyzing panels of SNPs polymorphic in archaic humans, which has been suggested as a solution for the ascertainment problem, has limited statistical power and retains important biases. However, by carrying out simulations of diverse demographic histories, we show that bias in inferences based on f-statistics can be minimized by ascertaining on variants common in a union of diverse African groups; such ascertainment retains high statistical power while allowing co-analysis of archaic and modern groups.

A quantile integral linear model to quantify genetic effects on phenotypic variability.

Detecting genetic variants associated with the variance of complex traits, that is, variance quantitative trait loci (vQTLs), can provide crucial insights into the interplay between genes and environments and how they jointly shape human phenotypes in the population. We propose a quantile integral linear model (QUAIL) to estimate genetic effects on trait variability. Through extensive simulations and analyses of real data, we demonstrate that QUAIL provides computationally efficient and statistically powerful vQTL mapping that is robust to non-Gaussian phenotypes and confounding effects on phenotypic variability. Applied to UK Biobank (n = 375,791), QUAIL identified 11 vQTLs for body mass index (BMI) that have not been previously reported. Top vQTL findings showed substantial enrichment for interactions with physical activities and sedentary behavior. Furthermore, variance polygenic scores (vPGSs) based on QUAIL effect estimates showed superior predictive performance on both population-level and within-individual BMI variability compared to existing approaches. Overall, QUAIL is a unified framework to quantify genetic effects on the phenotypic variability at both single-variant and vPGS levels. It addresses critical limitations in existing approaches and may have broad applications in future gene-environment interaction studies.

The evolution of mechanisms to produce phenotypic heterogeneity in microorganisms.

In bacteria and other microorganisms, the cells within a population often show extreme phenotypic variation. Different species use different mechanisms to determine how distinct phenotypes are allocated between individuals, including coordinated, random, and genetic determination. However, it is not clear if this diversity in mechanisms is adaptive-arising because different mechanisms are favoured in different environments-or is merely the result of non-adaptive artifacts of evolution. We use theoretical models to analyse the relative advantages of the two dominant mechanisms to divide labour between reproductives and helpers in microorganisms. We show that coordinated specialisation is more likely to evolve over random specialisation in well-mixed groups when: (i) social groups are small; (ii) helping is more "essential"; and (iii) there is a low metabolic cost to coordination. We find analogous results when we allow for spatial structure with a more detailed model of cellular filaments. More generally, this work shows how diversity in the mechanisms to produce phenotypic heterogeneity could have arisen as adaptations to different environments.

Mitochondrial-nuclear epistasis underlying phenotypic variation in breast cancer pathology.

The interplay between genes harboring single nucleotide polymorphisms (SNPs) is vital to better understand underlying contributions to the etiology of breast cancer. Much attention has been paid to epistasis between nuclear genes or mutations in the mitochondrial genome. However, there is limited understanding about the epistatic effects of genetic variants in the nuclear and mitochondrial genomes jointly on breast cancer. We tested the interaction of germline SNPs in the mitochondrial (mtSNPs) and nuclear (nuSNPs) genomes of female breast cancer patients in The Cancer Genome Atlas (TCGA) for association with morphological features extracted from hematoxylin and eosin (H&E)-stained pathology images. We identified 115 significant (q-value < 0.05) mito-nuclear interactions that increased nuclei size by as much as 12%. One interaction between nuSNP rs17320521 in an intron of the WSC Domain Containing 2 (WSCD2) gene and mtSNP rs869096886, a synonymous variant mapped to the mitochondrially-encoded NADH dehydrogenase 4 (MT-ND4) gene, was confirmed in an independent breast cancer data set from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC). None of the 10 mito-nuclear interactions identified from non-diseased female breast tissues from the Genotype-Expression (GTEx) project resulted in an increase in nuclei size. Comparisons of gene expression data from the TCGA breast cancer patients with the genotype homozygous for the minor alleles of the SNPs in WSCD2 and MT-ND4 versus the other genotypes revealed core transcriptional regulator interactions and an association with insulin. Finally, a Cox proportional hazards ratio = 1.7 (C.I. 0.98-2.9, p-value = 0.042) and Kaplan-Meier plot suggest that the TCGA female breast cancer patients with low gene expression of WSCD2 coupled with large nuclei have an increased risk of mortality. The intergenomic dependency between the two variants may constitute an inherent susceptibility of a more severe form of breast cancer and points to genetic targets for further investigation of additional determinants of the disease.

Survey on phenotypic resistance in Enterococcus faecalis: comparison between the expression of biofilm-associated genes in Enterococcus faecalis persister and non-persister cells.

BACKGROUND: Phenotypic resistance is considered as a serious therapeutic challenge for which a definitive remedy has not been discovered yet. Biofilm and persister cell formation are two well-studied phenotypic resistance phenomena, leading to the recalcitrance and relapse of different types of chronic infections. The presence of persister cells in biofilm structures seems to be one of the main factors contributing to the relapse of infections and treatment failure. Given the dormant and inert nature of persister cells, they can be easy targets for the immune system factors. Biofilm formation can be a survival strategy for the defenseless persister cells. Thus, this study was aimed to evaluate the expression of biofilm-associated genes in Enterococcus faecalis persister and non-persister cells. METHODS: Vancomycin susceptibility and biofilm formation ability were investigated among 95 E. faecalis clinical isolates using microtiter broth dilution and microtiter plate assays, respectively. PCR was used to determine the presence of biofilm-related genes (gelE, esp, and agg) among the vancomycin-susceptible, biofilm producer E. faecalis isolates (91 isolates). Minimum bactericidal concentration for biofilms (MBCB) were determined for vancomycin using the MTP assay. Bacterial persister assay was performed using an enzymatic lysis assay. Finally, the expression of biofilm-related genes was compared between the persister and non-persister isolates of E. faecalis using real-time qPCR. RESULTS: E. faecalis isolates showed a high level of susceptibility (95.8%) to vancomycin (MIC < 1 µg/mL). The gelE, esp, and agg genes were found in 91 (100%), 72 (79.12), and 74 (81.32) of the isolates, respectively. All the E. faecalis isolates were tolerant to vancomycin in the biofilm condition, showing a MBCB of > 2500 µg/mL. Based on the enzymatic lysis assay, only 3 isolates, out of the 91, had the ability to form persister cells. The expression of biofilm-associated genes was higher among the persister compared to non-persister E. faecalis isolates. CONCLUSIONS: Biofilm-associated persister cells indicated a high vancomycin tolerance compared to non-persister cells. Moreover, persister isolates showed a higher tendency for biofilm formation and a higher expression level of the biofilm-associated genes, compared to non-persister isolates.

Cardiomiopatia Hipertrófica: uma revisão pelo olhar da ressonância magnética / Hypertrophic Cardiomyopathy: a review using magnetic resonance imaging

A cardiomiopatia hipertrófica é a cardiopatia genética mais frequente na população geral e é caracterizada por uma hipertrofia ventricular esquerda assimétrica. Entretanto, as alterações fenotípicas desta cardiomiopatia vão muito além da hipertrofia ventricular, e incluem alterações do aparato valvar mitral, dos músculos papilares e do ventrículo direito. Devido à dificuldade no diagnóstico diferencial entre as múltiplas causas de hipertrofia, a ressonância magnética cardíaca vem cumprindo um papel fundamental na avaliação diagnóstica e prognóstica desta cardiomiopatia. A cineressonância magnética na definição da localização e extensão da hipertrofia, o realce tardio, na detecção das áreas de fibrose miocárdica e técnicas mais recentes como o Mapa de T1 que avalia a fibrose intersticial e o volume extracelular; e finalmente o Tissue Tracking na análise da deformação miocárdica.(AU)

Hypertrophic cardiomyopathy, the most common genetic cardiopathy in the general population, is characterized by asymmetric left ventricular hypertrophy. However, the phenotypic changes in this cardiomyopathy extend beyond ventricular hypertrophy and include changes in the mitral valve apparatus, papillary muscles, and right ventricle. Due to the difficult differential diagnosis among multiple causes of hypertrophy, cardiac magnetic resonance has played a fundamental role in its diagnostic and prognostic evaluation; magnetic cine-resonance in defining the location and extent of hypertrophy; late enhancement, in the detection of areas of myocardial fibrosis; more recent techniques such as T1 mapping that assesses interstitial fibrosis and extracellular volume; and finally tissue tracking in the analysis of myocardial deformation. (AU)

The genetic architecture of DNA replication timing in human pluripotent stem cells.

DNA replication follows a strict spatiotemporal program that intersects with chromatin structure but has a poorly understood genetic basis. To systematically identify genetic regulators of replication timing, we exploited inter-individual variation in human pluripotent stem cells from 349 individuals. We show that the human genome's replication program is broadly encoded in DNA and identify 1,617 cis-acting replication timing quantitative trait loci (rtQTLs) - sequence determinants of replication initiation. rtQTLs function individually, or in combinations of proximal and distal regulators, and are enriched at sites of histone H3 trimethylation of lysines 4, 9, and 36 together with histone hyperacetylation. H3 trimethylation marks are individually repressive yet synergistically associate with early replication. We identify pluripotency-related transcription factors and boundary elements as positive and negative regulators of replication timing, respectively. Taken together, human replication timing is controlled by a multi-layered mechanism with dozens of effectors working combinatorially and following principles analogous to transcription regulation.

Influence of CYP2C9 Polymorphisms on Plasma Concentration of Warfarin and 7-Hydroxy Warfarin in South Indian Patients.

BACKGROUND: Warfarin is primarily metabolized by cytochrome P450 2C9 (CYP2C9) enzyme, which is encoded by the CYP2C9 gene. CYP2C9*2 and CYP2C9*3 variants significantly influence warfarin metabolism and subsequently the required dose of warfarin. OBJECTIVES: The current retrospective study was aimed to determine the influence of CYP2C9 variants on warfarin metabolic ratio (MR, warfarin/7-hydroxy warfarin) and warfarin maintenance therapy in 210 patients (mean age 44.6±11.6 (SD) years; male to female ratio 81:129). METHODS: High-performance liquid chromatography (HPLC) with UV detector was used to measure plasma concentrations of warfarin and 7-hydroxy warfarin. Plasma samples were collected 12 h after the previous dose of warfarin was administered. CYP2C9 variants (rs1799853 and rs1057910) were identified using real-time polymerase chain reaction allele-discrimination method. RESULTS: The mean daily maintenance dose of warfarin was 4.6±1.8 (SD) mg. The mean plasma warfarin and 7-hydroxy warfarin concentrations were 3.7±1.6 (SD) µg/mL and 1.1±0.54 (SD) µg/mL, respectively. Patients carrying other CYP2C9 variants required 39% lower warfarin maintenance dose 3.3±1.2(SD)mg than CYP2C9*1*1 carrier 4.9±1.8(SD)mg, (p<0.0001). MRs differed significantly between CYP2C9 variant carriers (8.1±5.1) and normal genotype carriers (4.8±3.9) (p<0.0001). Probit analysis identified an MR value of 7.6 as the anti-mode (sensitivity of 84% and specificity of 55%) to differentiate poor and intermediate metabolizers (carriers of any CYP2C9*2 or CYP2C9*3 variants) from normal metabolizers (CYP2C9*1*1 genotype). CONCLUSION: The present study results provide, insights on the effect of CYP2C9 genetic polymorphisms on inter-individual variability in warfarin metabolism and emphasizes utility of phenotyping in a setting of genotype-guided dosing of warfarin in South Indian population.

Theoretical Formulation Strategies towards Neutralizing Inter-individual Variability Associated with Tacrolimus Immunosuppressant Therapy: A Case Study on Nextgeneration Personalized Medicine.

Individualizing drug therapy and attaining maximum benefits of a drug devoid of adverse reactions is the benefit of personalized medicine. One of the important factors contributing to inter-individual variability is genetic polymorphism. As of now, dose titration is the only followed golden standard for implementing personalized medicine. Converting the genotypic data into an optimized dose has become easier now due to technology development. However, for many drugs, finding an individualized dose may not be successful, which further leads to a trial and error approach. These dose titration strategies are generally followed at the clinical level, and so industrial involvement and further standardizations are not feasible. On the other side, technologically driven pharmaceutical industries have multiple smart drug delivery systems which are underutilized towards personalized medicine. Transdisciplinary research with drug delivery science can additionally support the personalization by converting the traditional concept of "dose titration towards personalization" with novel "dose-cum-dosage form modification towards next-generation personalized medicine"; the latter approach is useful to overcome gene-based inter-individual variability by either blocking, to downregulate, or bypassing the biological protein generated by the polymorphic gene. This article elaborates an advanced approach to implementing personalized medicine with the support of novel drug delivery systems. As a case study, we further reviewed the genetic polymorphisms associated with tacrolimus and customized novel drug delivery systems to overcome these challenges factored towards personalized medicine for better clinical outcomes, thereby paving a new strategy for implementing personalized medicine for all other drug candidates.

Phenotypic Diversity of Root Characteristics in Recombinant Inbred Lines of Cross Between Lowland and Highland Rice Varieties for Drought Tolerance Potential.

<b>Background and Objective:</b> Breeding between highland and lowland rice varieties is one of the strategic breeding of lowland rice for enhancing drought-tolerant capacity through root structure improvement. The objective of this study was to evaluate the phenotypic diversity of rice root traits in pot screening compared to the lowland parent. <b>Materials and Methods:</b> The basket method was utilized in pot cultivation to evaluate the 100 of F7 Recombinant Inbred Lines (RILs) derived through single seed descent method from a cross between lowland rice, RD49 variety and upland rice, Payaleumgaeng (PLG) variety. The two parents and F7 progenies were evaluated for the number of shallow roots (SRN) and the number of deep roots (DRN), together with other traits which were the number of total roots (TRN), the Ratio of Deep Rooting (RDR), maximum Root Length (RL), Root Dry Weight (RDW), Shoot Dry Weight (SDW), the ratio of Root to Shoot Weight (RSR) and Plant Height (PH). <b>Results:</b> The result showed that PLG had significantly higher SRN, DRN, TRN and RDR than RD49. The distribution of these traits showed slightly positive skewness in DRN, RDR, RDW, SDW and RSR and negative skewness in SRN, TRN, RL and PH. However, some lines in this RIL population displayed better performance of root traits compared to both parents. Principal Component Analysis (PCA) of DRN, SRN, TRN and RDR in this population showed a distinctly different pattern among both parents. Most of the selected lines had superior RDR over RD49 and had various root characteristics patterns due to the diverse PCA coordinates. The yield trial of some breeding lines in this cross show superior yield over RD49 under drought-prone cultivation area. <b>Conclusion:</b> This study showed broad phenotypic diversity in the population constructed through single seed descent selection for enhancing deep root structure in rice for drought adaptation.

NBS1 I171V variant underlies individual differences in chromosomal radiosensitivity within human populations.

Genetic information is protected against a variety of genotoxins including ionizing radiation (IR) through the DNA double-strand break (DSB) repair machinery. Genome-wide association studies and clinical sequencing of cancer patients have suggested that a number of variants in the DNA DSB repair genes might underlie individual differences in chromosomal radiosensitivity within human populations. However, the number of established variants that directly affect radiosensitivity is still limited. In this study, we performed whole-exome sequencing of 29 Japanese ovarian cancer patients and detected the NBS1 I171V variant, which is estimated to exist at a rate of approximately 0.15% in healthy human populations, in one patient. To clarify whether this variant indeed contributes to chromosomal radiosensitivity, we generated NBS1 I171V variant homozygous knock-in HCT116 cells and mice using the CRISPR/Cas9 system. Radiation-induced micronucleus formation and chromosomal aberration frequency were significantly increased in both HCT116 cells and mouse embryonic fibroblasts (MEFs) with knock-in of the NBS1 I171V variant compared with the levels in wild-type cells. These results suggested that the NBS1 I171V variant might be a genetic factor underlying individual differences in chromosomal radiosensitivity.

Genotype Phenotype Correlation in Dent Disease 2 and Review of the Literature: OCRL Gene Pleiotropism or Extreme Phenotypic Variability of Lowe Syndrome?

Dent disease is a rare X-linked renal tubulopathy due to CLCN5 and OCRL (DD2) mutations. OCRL mutations also cause Lowe syndrome (LS) involving the eyes, brain and kidney. DD2 is frequently described as a mild form of LS because some patients may present with extra-renal symptoms (ESs). Since DD2 is a rare disease and there are a low number of reported cases, it is still unclear whether it has a clinical picture distinct from LS. We retrospectively analyzed the phenotype and genotype of our cohort of 35 DD2 males and reviewed all published DD2 cases. We analyzed the distribution of mutations along the OCRL gene and evaluated the type and frequency of ES according to the type of mutation and localization in OCRL protein domains. The frequency of patients with at least one ES was 39%. Muscle findings are the most common ES (52%), while ocular findings are less common (11%). Analysis of the distribution of mutations revealed (1) truncating mutations map in the PH and linker domain, while missense mutations map in the 5-phosphatase domain, and only occasionally in the ASH-RhoGAP module; (2) five OCRL mutations cause both DD2 and LS phenotypes; (3) codon 318 is a DD2 mutational hot spot; (4) a correlation was found between the presence of ES and the position of the mutations along OCRL domains. DD2 is distinct from LS. The mutation site and the mutation type largely determine the DD2 phenotype.

Genetic landscape of 125 pharmacogenes in Chinese from the Chinese Millionome Database.

Inter-individual differences of drug responses could be attributed to genetic variants of pharmacogenes such as cytochrome P450 (CYP), phase 2 enzymes, and transporters. In contrast to extensive studies on the genetic polymorphisms of CYP gene, genetic mutation spectrum of other pharmacogenes was under-representative in the pharmacogenetics investigations. Here we studied the genetic variations of 125 pharmacogenes including drug transporters, non-CYP phase 1 enzymes, phase 2 enzymes, nuclear receptors and others in Chinese from the Chinese Millionome Database (CMDB), of which 38,188 variants were identified. Computational analyses of the 2554 exonic variants found 617 deleterious missense variants, 91.1% of which were rare, and of the 54 loss-of-function (splice acceptor, splice donor, start lost, and stop gained) variants, 53 (98.1%) were rare. These results suggested an enrichment of rare variants in functional ones for pharmacogenes. Certain common functional variants including NUDT15 13:48611934 G/A (rs186364861), UGT1A1 2:234676872 C/T (rs34946978), and ALDH2 12:112241766 G/A (rs671) were population-specific for CMDB Chinese because they were absent (with a zero of variant allele frequency) or very rare in other gnomAD populations. These findings might be useful for the further pharmacogenomics research and clinical application in Chinese.

Data integration uncovers the metabolic bases of phenotypic variation in yeast.

The relationship between different levels of integration is a key feature for understanding the genotype-phenotype map. Here, we describe a novel method of integrated data analysis that incorporates protein abundance data into constraint-based modeling to elucidate the biological mechanisms underlying phenotypic variation. Specifically, we studied yeast genetic diversity at three levels of phenotypic complexity in a population of yeast obtained by pairwise crosses of eleven strains belonging to two species, Saccharomyces cerevisiae and S. uvarum. The data included protein abundances, integrated traits (life-history/fermentation) and computational estimates of metabolic fluxes. Results highlighted that the negative correlation between production traits such as population carrying capacity (K) and traits associated with growth and fermentation rates (Jmax) is explained by a differential usage of energy production pathways: a high K was associated with high TCA fluxes, while a high Jmax was associated with high glycolytic fluxes. Enrichment analysis of protein sets confirmed our results. This powerful approach allowed us to identify the molecular and metabolic bases of integrated trait variation, and therefore has a broad applicability domain.

NUDT15 polymorphism influences the metabolism and therapeutic effects of acyclovir and ganciclovir.

Nucleobase and nucleoside analogs (NNA) are widely used as anti-viral and anti-cancer agents, and NNA phosphorylation is essential for the activity of this class of drugs. Recently, diphosphatase NUDT15 was linked to thiopurine metabolism with NUDT15 polymorphism associated with drug toxicity in patients. Profiling NNA drugs, we identify acyclovir (ACV) and ganciclovir (GCV) as two new NNAs metabolized by NUDT15. NUDT15 hydrolyzes ACV and GCV triphosphate metabolites, reducing their effects against cytomegalovirus (CMV) in vitro. Loss of NUDT15 potentiates cytotoxicity of ACV and GCV in host cells. In hematopoietic stem cell transplant patients, the risk of CMV viremia following ACV prophylaxis is associated with NUDT15 genotype (P = 0.015). Donor NUDT15 deficiency is linked to graft failure in patients receiving CMV-seropositive stem cells (P = 0.047). In conclusion, NUDT15 is an important metabolizing enzyme for ACV and GCV, and NUDT15 variation contributes to inter-patient variability in their therapeutic effects.

Tone and genes: New cross-linguistic data and methods support the weak negative effect of the "derived" allele of ASPM on tone, but not of Microcephalin.

While it is generally accepted that language and speech have genetic foundations, and that the widespread inter-individual variation observed in many of their aspects is partly driven by variation in genes, it is much less clear if differences between languages may also be partly rooted in our genes. One such proposal is that the population frequencies of the so-called "derived" alleles of two genes involved in brain growth and development, ASPM and Microcephalin, are related to the probability of speaking a tone language or not. The original study introducing this proposal used a cross-linguistic statistical approach, showing that these associations are "special" when compared with many other possible relationships between genetic variants and linguistic features. Recent experimental evidence supports strongly a negative effect of the "derived" allele of ASPM on tone perception and/or processing within individuals, but failed to find any effect for Microcephalin. Motivated by these experimental findings, I conduct here a cross-linguistic statistical test, using a larger and updated dataset of 175 samples from 129 unique (meta)populations, and a battery of methods including mixed-effects regression (Bayesian and maximum-likelihood), mediation and path analysis, decision trees and random forests, using permutations and restricted sampling to control for the confounding effects of genealogy (language families) and contact (macroareas). Overall, the results support a negative weak effect of ASPM-D against the presence of tone above and beyond the strong confounding influences of genealogy and contact, but they suggest that the original association between tone and MCPH1 might have been a false positive, explained by differences between populations and languages within and outside Africa. Thus, these cross-linguistic population-scale statistical results are fully consonant with the inter-individual-level experimental results, and suggest that the observed linguistic diversity may be, at least in some cases, partly driven by genetic diversity.

Craniofacial features of 3q29 deletion syndrome: Application of next-generation phenotyping technology.

3q29 deletion syndrome (3q29del) is a recurrent deletion syndrome associated with neuropsychiatric disorders and congenital anomalies. Dysmorphic facial features have been described but not systematically characterized. This study aims to detail the 3q29del craniofacial phenotype and use a machine learning approach to categorize individuals with 3q29del through analysis of 2D photos. Detailed dysmorphology exam and 2D facial photos were ascertained from 31 individuals with 3q29del. Photos were used to train the next-generation phenotyping algorithm DeepGestalt (Face2Gene by FDNA, Inc, Boston, MA) to distinguish 3q29del cases from controls and all other recognized syndromes. Area under the curve of receiver operating characteristic curves (AUC-ROC) was used to determine the capacity of Face2Gene to identify 3q29del cases against controls. In this cohort, the most common observed craniofacial features were prominent forehead (48.4%), prominent nose tip (35.5%), and thin upper lip vermillion (25.8%). The FDNA technology showed an ability to distinguish cases from controls with an AUC-ROC value of 0.873 (p = 0.006) and led to the inclusion of 3q29del as one of the supported syndromes. This study found a recognizable facial pattern in 3q29del, as observed by trained clinical geneticists and next-generation phenotyping technology. These results expand the potential application of automated technology such as FDNA in identifying rare genetic syndromes, even when facial dysmorphology is subtle.

An intrafamilial phenotypic variability in Ellis-Van Creveld syndrome due to a novel 27 bps deletion mutation.

Ellis-van Creveld (EvC) syndrome is an autosomal recessive disease, characterized by ectodermal, skeletal, and cardiac anomalies. We report intrafamilial phenotypic variability in three new EvC syndrome cases. Affected males in this study showed only ectodermal abnormalities, whereas an affected female showed the classical presentation of EvC Syndrome, including bilateral postaxial polydactyly of hands and feet, and congenital heart defects. Whole exome sequencing was performed to identify the causative variant, followed by validation and segregation analysis using Sanger sequencing. A homozygous deletion variant (c.731_757del) was identified in exon 6 of the EVC gene (NM_153717.2). The identified variant is considered to be the most likely candidate variant for the EvC syndrome in the family based on previous reports validating the role of EVC variants in the EvC syndrome. The disease correctly segregated in the family members, as all affected members were homozygous, and obligate carriers were heterozygous. Our family is remarkable in highlighting the variable expressivity of the EvC phenotype within the same family, due to a homozygous deletion mutation in the EVC gene. The variable expressivity might be due to the hypomorphic nature of mutation, or the presence of additional variants in modifier genes or in the regulatory regions of the EVC/EVC2 genes.

Identification of high-dimensional omics-derived predictors for tumor growth dynamics using machine learning and pharmacometric modeling.

Pharmacometric modeling can capture tumor growth inhibition (TGI) dynamics and variability. These approaches do not usually consider covariates in high-dimensional settings, whereas high-dimensional molecular profiling technologies ("omics") are being increasingly considered for prediction of anticancer drug treatment response. Machine learning (ML) approaches have been applied to identify high-dimensional omics predictors for treatment outcome. Here, we aimed to combine TGI modeling and ML approaches for two distinct aims: omics-based prediction of tumor growth profiles and identification of pathways associated with treatment response and resistance. We propose a two-step approach combining ML using least absolute shrinkage and selection operator (LASSO) regression with pharmacometric modeling. We demonstrate our workflow using a previously published dataset consisting of 4706 tumor growth profiles of patient-derived xenograft (PDX) models treated with a variety of mono- and combination regimens. Pharmacometric TGI models were fit to the tumor growth profiles. The obtained empirical Bayes estimates-derived TGI parameter values were regressed using the LASSO on high-dimensional genomic copy number variation data, which contained over 20,000 variables. The predictive model was able to decrease median prediction error by 4% as compared with a model without any genomic information. A total of 74 pathways were identified as related to treatment response or resistance development by LASSO, of which part was verified by literature. In conclusion, we demonstrate how the combined use of ML and pharmacometric modeling can be used to gain pharmacological understanding in genomic factors driving variation in treatment response.

Pharmacometrics-Based Considerations for the Design of a Pharmacogenomic Clinical Trial Assessing Irinotecan Safety.

PURPOSE: Pharmacometric models provide useful tools to aid the rational design of clinical trials. This study evaluates study design-, drug-, and patient-related features as well as analysis methods for their influence on the power to demonstrate a benefit of pharmacogenomics (PGx)-based dosing regarding myelotoxicity. METHODS: Two pharmacokinetic and one myelosuppression model were assembled to predict concentrations of irinotecan and its metabolite SN-38 given different UGT1A1 genotypes (poor metabolizers: CLSN-38: -36%) and neutropenia following conventional versus PGx-based dosing (350 versus 245 mg/m2 (-30%)). Study power was assessed given diverse scenarios (n = 50-400 patients/arm, parallel/crossover, varying magnitude of CLSN-38, exposure-response relationship, inter-individual variability) and using model-based data analysis versus conventional statistical testing. RESULTS: The magnitude of CLSN-38 reduction in poor metabolizers and the myelosuppressive potency of SN-38 markedly influenced the power to show a difference in grade 4 neutropenia (<0.5·109 cells/L) after PGx-based versus standard dosing. To achieve >80% power with traditional statistical analysis (χ2/McNemar's test, α = 0.05), 220/100 patients per treatment arm/sequence (parallel/crossover study) were required. The model-based analysis resulted in considerably smaller total sample sizes (n = 100/15 given parallel/crossover design) to obtain the same statistical power. CONCLUSIONS: The presented findings may help to avoid unfeasible trials and to rationalize the design of pharmacogenetic studies.