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bioRxiv2019

Combinatorial genetic analysis of a regulatory network reveals the importance of higher order epistasis for gene deletion phenotypes

We lack an understanding of how the full range of genetic variants that occur in individuals can interact. To address this shortcoming, here we combine diverse mutations between genes in a model regulatory network, the galactose (GAL) switch of budding yeast. The effects of thousands of pairs of mutations fall into a limited number of phenotypic classes. While these effects are mostly predictable using simple rules that capture the stereotypical genetic interactions of the network, some double mutants have unexpected outcomes including constituting alternative functional switches. Each of these harmonious genetic combinations exhibits altered dependency on other regulatory genes. These cases illustrate how both pairwise and higher epistasis determines gene essentiality and how combinations of mutations rewire regulatory networks. Together, our results provide an overview of how broad spectra of mutations interact, how these interactions can be predicted, and how diverse genetic solutions can achieve wild-type phenotypic behavior.

genetics↗

bioRxiv2019

Risk of recurrent pregnancy loss in the Ukrainian population using a combined effect of genetic variants

Recurrent pregnancy loss (RPL) affects nearly 5% of the women of reproductive age. Its heterogeneous and multifactorial nature complicate both diagnosis and treatment, as well as identification of the genetic contribution to RPL. Evidence about the aetiology of RPL is controversial; however, several biological mechanisms have been proposed. Given the current knowledge about the genetic susceptibility to idiopathic RPL, we aimed to evaluate the predictive ability of a combined variant panel to the risk of RPL in the Ukrainian sample of 114 cases and 106 healthy controls. We genotyped variants within the 12 genetic loci reflecting the main biological pathways involved in pregnancy maintenance: blood coagulation (F2, F5, F7, GP1A), hormonal regulation (ESR1, ADRB2), endometrium and placental function (ENOS, ACE), folate metabolism (MTHFR) and inflammatory response (IL6, IL8, IL10). We showed that a genetic risk score (GRS) calculated from the 12 variants was associated with an increased risk of RPL (odds ratio 1.56, 95% CI: 1.21,2.04, P=8.7x10-4). The receiver operator characteristic (ROC) analysis resulted in the area under the curve (AUC) of 0.64 (95% CI: 0.57, 0.72), indicating an improved ability of the GRS to classify women with and without RPL. In summary, implementation of the GRS approach can help defining women at higher risk to complex multifactorial conditions such as RPL. Future well-powered genome-wide association studies will help in the dissection of biological pathways not hypothesised previously for RPL and further improve the prediction and identification of those at risk for RPL.

genetics↗

bioRxiv2019

Effect of inbreeding on type 2 diabetes-related metabolites in a Dutch genetic isolate

Autozygosity, meaning inheritance of an ancestral allele in the homozygous state is known to lead bi-allelic mutations that manifest their effects through the autosomal recessive inheritance pattern. Autosomal recessive mutations are known to be the underlying cause of several Mendelian metabolic diseases, especially among the offspring of related individuals. In line with this, inbreeding coefficient of an individual as a measure of cryptic autozygosity among the general population is known to lead adverse metabolic outcomes including type 2 diabetes (T2DM), a multifactorial metabolic disease for which the recessive genetic causes remain unknown. In order to unravel such effects for multiple metabolic facades of the disease, we investigated the relationship between the excess of homozygosity and the metabolic signature of T2DM. We included a set of heritable 143 circulating markers associated with fasting glucose in a Dutch genetic isolate Erasmus Rucphen Family (ERF) of up to 2,580 individuals. We calculated individual whole genome-based, exome-based and pedigree-based inbreeding coefficients and tested their influence on the T2DM-related metabolites as well as T2DM risk factors. We also performed model supervised genome-wide association analysis (GWAS) for the metabolites which significantly correlate with inbreeding values. Inbreeding value of the population significantly and positively correlated with associated with risk factors of T2DM: body-mass index (BMI), glucose, insulin resistance, fasting insulin and waist-hip ratio. We found that inbreeding influenced 32.9% of the T2DM-related metabolites, clustering among chemical groups of lipoproteins, amino-acids and phosphatidylcholines, whereas 80 % of these significant associations were independent of the BMI. The most remarkable effect of inbreeding is observed for S-HDL-ApoA1, for which we show evidence of the novel DISP1 genetic region discovered by model supervised GWAS, in the ERF population. In conclusion, we show that inbreeding effects human metabolism and genetic models other than the globally used additive model is worth considering for study of metabolic phenotypes.

genetics↗

bioRxiv2019

High diagnostic yield and clinical utility of WES for patients with undiagnosed genetic disorder by automating variant interpretation

PurposeEVIDENCE, an automated interpretation system, has been developed to facilitate the entire process of whole exome sequencing (WES) analyses. This study investigated the diagnostic yield of EVIDENCE in patients suspected genetic disorders. MethodsDNA from 330 probands (age range, 0-68 years) with suspected genetic disorders were subjected to WES. Candidate variants were identified by EVIDENCE and confirmed by testing family members and/or clinical reassessments. ResultsThe average number of overlapping organ categories per patient was 4.5 {+/-} 5.0. EVIDENCE reported a total 244 variants in 215 (65.1%) of the 330 probands. After clinical reassessment and/or family member testing, 196 variants were identified in 171 probands (51.8%), including 115 novel variants. These variants were confirmed as being responsible for 146 genetic disorders. One hundred-seven (54.6%) of the 196 variants were categorized as pathogenic or likely pathogenic before, and 146 (74.6%) after, clinical assessment and/or family member testing. Factors associated with a variant being confirmed as causative include rules, such as PVS1, PS1, PM1, PM5, and PP5, and similar symptom scores between that variant and a patients phenotype. ConclusionThis new, automated variant interpretation system facilitated the diagnosis of various genetic diseases with a 51% improvement in diagnostic yield.

genetics↗

bioRxiv2019

Genetic basis of susceptibility to Diplodia sapinea and Armillaria ostoyae in maritime pine

Forest ecosystems are increasingly challenged by extreme events, e.g. drought, storms, pest and pathogenic fungi outbreaks, causing severe ecological and economical losses. Understanding the genetic basis of adaptive traits in tree species is of key importance to preserve forest ecosystems, as genetic variation in a trait (i.e. heritability) determines its potential for human-mediated or evolutionary change. Maritime pine (Pinus pinaster Aiton), a conifer widely distributed in southwestern Europe and northwestern Africa, grows under contrasted environmental conditions promoting local adaptation. Genetic variation at adaptive phenotypes, including height, growth phenology and susceptibility to two fungal pathogens (Diplodia sapinea and Armillaria ostoyae) and an insect pest (Thaumetopoea pityocampa), were assessed in a range-wide clonal common garden of maritime pine. Broad-sense heritability was significant for height (0.219), growth phenology (0.165-0.310) and pathogen susceptibility (necrosis length caused by D. sapinea, 0.152; and by A. ostoyae, 0.021) measured after inoculation under controlled conditions, but not for pine processionary moth incidence in the common garden. The correlations of trait variation among populations revealed contrasting trends for pathogen susceptibility to D. sapinea and A. ostoyae with respect to height. Taller trees showed longer necrosis length caused by D. sapinea while shorter trees were more affected by A. ostoyae. Moreover, maritime pine populations from areas with high summer temperatures and frequent droughts were less susceptible to D. sapinea but more susceptible to A. ostoyae. Finally, an association study using 4,227 genome-wide SNPs revealed several loci significantly associated to each trait (range of 3-26), including a possibly disease-induced translation initiation factor, eIF-5. This study provides important insights to develop genetic conservation and breeding strategies integrating species responses to biotic stressors.

genetics↗

bioRxiv2019

Congenital Zika Syndrome is associated with maternal genetic background

BackgroundHost factors that influence Congenital Zika Syndrome (CZS) outcome remain elusive. Interferons have been reported as the main antiviral factor in Zika and other flavivirus infections. MethodsWe accessed samples from Zika pregnancies, conducted a case-control study to verify whether interferon alfa receptor 1 (IFNAR1) and interferon lambda 2 and 4 (IFNL2/4) single nucleotide polymorphisms (SNPs) contribute to CZS newborn outcome and we characterized placenta gene expression profile at term. FindingsNewborns carrying CG/CC genotypes of rs2257167 in IFNAR1 presented higher risk of developing CZS (OR=3.73; IC=1.36-10.21; Pcorrected=0.02646). No association between IFNL SNPs and CZS was observed. Placenta from CZS cases displayed lower levels of IFNL2 and ISG15 along with higher IFIT5. The rs2257167 CG/CC placentas also demonstrated high levels of IFIT5 and inflammation-related genes. InterpretationWe found CZS to be related with exacerbated type I IFN and insufficient type III IFN in placenta at term, forming an unbalanced response modulated by the IFNAR1 rs2257167 genotype. These findings shed light on the host-pathogen interaction focusing on the genetically regulated type I / type III IFN axis that could lead to better management of Zika and other TORCH (Toxoplasma, Others, Rubella, Cytomegalovirus, Herpes) congenital infections. FundingThis work was supported by the Instituto Oswaldo Cruz (Rio de Janeiro, Brazil) and by the Instituto de Tecnologia em Imunobiologicos (Rio de Janeiro, Brazil). Research in contextO_ST_ABSEvidence before this studyC_ST_ABSLevels of type I and type III interferons are genetically controlled and decisively regulate outcome of spontaneous viral infections or response to antiviral treatment. Hepatitis C virus, Yellow Fever and Zika virus belong to the Flaviviridae family and elicit similar host immune responses. Congenital Zika Syndrome presents well-known risk factors, mainly the first trimester of pregnancy as well as social and nutritional factors, however, these do not entirely explain abnormal outcomes. Added value of this studyWe conducted a case-control study to evaluate SNPs in type I and III interferon genes using samples from newborns and mothers who had zika infection during pregnancy. We have shown that newborn interferon type I background contributes to the development of abnormal CSZ. This specific genetic makeup regulates placental immunological responses and prevents an exacerbated type I, and lack of type III, interferon response in syndromic cases. Implications of all the available evidenceOur study suggests an important factor regulating the host-pathogen interaction during Zika virus (ZIKV) infections in humans. During pregnancy, genetic variations play a role in balancing tissue-specific type I and III interferons during ZIKV congenital infection influencing fetal neurological damage. Custom pharmacological interventions could be used to modulate immunity and inflammation towards protective responses. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/715862v3_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@ee554forg.highwire.dtl.DTLVardef@122c773org.highwire.dtl.DTLVardef@547695org.highwire.dtl.DTLVardef@13543db_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

bioRxiv2019

Reshaping the Hexagone: the genetic landscape of modern France

Unlike other European countries, the human population genetics and demographic history of Metropolitan France is surprisingly understudied. In this work, we combined newly genotyped samples from various zones in France with publicly available data and applied both allele frequency and haplotype-based methods in order to describe the internal structure of this country, by using genome-wide single nucleotide polymorphism (SNP) array genotypes. We found out that French Basques are genetically distinct from all other populations in the Hexagone and that the populations from southwest France (namely the Gascony region) share a large proportion of their ancestry with Basques. Otherwise, the genetic makeup of the French population is relatively homogeneous and mostly related to Southern and Central European groups. However, a fine-grained, haplotype-based analysis revealed that Bretons slightly separated from the rest of the groups, due mostly to gene flow from the British Isles in a time frame that coincides both historically attested Celtic population movements to this area between the 3th and the 9th centuries CE, but also with a more ancient genetic continuity between Brittany and the British Isles related to the shared drift with hunter-gatherer populations. Haplotype-based methods also unveiled subtle internal structures and connections with the surrounding modern populations, particularly in the periphery of the Hexagone.

genetics↗

bioRxiv2019

The paternal and maternal genetic history of Vietnamese populations

Vietnam exhibits great cultural and linguistic diversity, yet the genetic history of Vietnamese populations remains poorly understood. Previous studies focused mostly on the majority Kinh group, and thus the genetic diversity of the many other groups has not yet been investigated. Here we analyze complete mtDNA genome sequences and 2.34 mB sequences of the male-specific portion of the Y chromosome from the Kinh and 16 minority populations, encompassing all five language families present in Vietnam. We find highly variable levels of diversity within and between groups that do not correlate with either geography or language family. In particular, the Mang and Sila have undergone recent, independent bottlenecks, while the majority group, Kinh, exhibits low levels of differentiation with other groups. The two Austronesian-speaking groups, Giarai and Ede, show a potential impact of matrilocality on their patterns of variation. Overall, we find that isolation, coupled with some limited contact involving some groups, has been the major factor influencing the genetic structure of Vietnamese populations, and that there is substantial genetic diversity that is not represented by the Kinh.

genetics↗

bioRxiv2019

High-resolution QTL mapping with Diversity Outbred mice identifies genetic variants that impact gut microbiome composition

The composition of the gut microbiome is impacted by a complex array of factors, from nutrient composition and availability, to physical factors like temperature, pH, and flow rate, as well as interactions among the members of the microbial community. Many of these factors are affected by the host, raising the question of how host genetic variation impacts microbiome composition. Though human studies confirm this type of role for host genetics, its overall importance is still a subject of debate and remains difficult to study. The mouse model, by allowing the strict control of genetics, nutrition, and other environmental factors, has provided an excellent opportunity to extend this work, and the Diversity Outbred (DO) mice in particular present a chance to pinpoint host genetic variants that influence microbiome composition at different levels of generality. Here, we apply 16S rRNA gene sequencing to fecal samples of 247 DO male mice to estimate heritability and perform taxon-specific QTL mapping of microbial relative abundances revealing an increasingly heterogeneous picture of host function and microbial taxa at the host-microbiome interface. We present the first report of significant heritability of phylum Tenericutes in mice, and find novel QTL-spanning genes involved in antibacterial pathways, immune and inflammatory disease, and lipid metabolism.

genetics↗

bioRxiv2019

Overlapping Genetic Architecture between Parkinson Disease and Melanoma

Epidemiologic studies have reported inconsistent results regarding an association between Parkinson disease (PD) and cutaneous melanoma (melanoma). Identifying shared genetic architecture between these diseases can support epidemiologic findings and identify common risk genes and biological pathways. Here we apply polygenic, linkage disequilibrium-informed methods to the largest available case-control, genome-wide association study summary statistic data for melanoma and PD. We identify positive and significant genetic correlation (correlation: 0.17, 95% CI 0.10 to 0.24; P = 4.09 x 10-06) between melanoma and PD. We further demonstrate melanoma and PD-inferred gene expression to overlap across tissues (correlation: 0.14, 95% CI 0.06 to 0.22; P = 7.87 x 10-04), and highlight seven genes including PIEZO1, TRAPPC2L, and SOX6 as potential mediators of the genetic correlation between melanoma and PD. These findings demonstrate specific, shared genetic architecture between PD and melanoma that manifests at the level of gene expression.

genetics↗

bioRxiv2019

Population genetics of Bull Trout ( Salvelinus confluentus ) in the Upper Athabasca river basin

Across its native range, Bull Trout (Salvelinus confluentus) extent and abundance are in decline due to historic overharvest and habitat degradation. Because Bull Trout are dependent on extensively connected, cold, clean headwater habitats, fragmentation from land use changes causes difficulty when determining the true extent and health of their populations, with Bull Trout of Albertas Eastern Slope region being no exception. Across this region, 431 Bull Trout from 20 sites were sampled from the Athabasca and Saskatchewan River basins and compared using 10 microsatellite loci to characterize within- and among-population genetic variation. The Saskatchewan and Athabasca River basins contained similar levels of heterozygosity but were differentiated from one another. Within the Athabasca River basin, five genetically differentiated clusters were found. Additionally, no isolation-by-distance pattern was observed between these sites. These results suggest these populations have ample genetic diversity, but genetic differentiation should be considered when deciding whether and how to alter connectivity between populations.

genetics↗

bioRxiv2019

Genetic effect estimates in case-control studies when a continuous variable is omitted from the model

Large-scale genome-wide analyses scans provide massive volumes of genetic variants on large number of cases and controls that can be used to estimate the genetic effects. Yet, the sets of non-genetic variables available in publicly available databases are often brief. It is known that omitting a continuous variable from a logistic regression model can result in biased estimates of odds ratios (OR) (e.g., Gail et al (1984), Neuhaus et al (1993), Hauck et al (1991), Zeger et al (1988)). We are interested to assess what information is needed to recover the bias in the OR estimate of genotype due to omitting a continuous variable in settings when the actual values of the omitted variable are not available. We derive two estimating procedures that can recover the degree of bias based on a conditional density of the omitted variable or knowing the distribution of the omitted variable. Importantly, our derivations show that omitting a continuous variable can result in either under- or over-estimation of the genetic effects. We performed extensive simulation studies to examine bias, variability, false positive rate, and power in the model that omits a continuous variable. We show the application to two genome-wide studies of Alzheimers disease.\n\nData Availability StatementThe data that support the findings of this study are openly available in the Database of Genotypes and Phenotypes at [https://www.ncbi.nlm.nih.gov/projects/gap/cgibin/study.cgi?study_id=phs000372.v1.p1], reference number [phs000372.v1.p1] and at the Alzheimers Disease Neuroimaging Initiative http://adni.loni.usc.edu/.

genetics↗

bioRxiv2019

Early metabolic features of genetic liability to type 2 diabetes: cohort study with repeated metabolomics across early life

BackgroundType 2 diabetes develops for many years before diagnosis. We aimed to reveal early metabolic features characterising liability to adult disease by examining genetic liability to adult type 2 diabetes in relation to detailed metabolic traits across early life.\n\nMethods and FindingsData were from up to 4,761 offspring from the Avon Longitudinal Study of Parents and Children cohort. Linear models were used to examine effects of a genetic risk score (GRS, including 162 variants) for adult type 2 diabetes on 4 repeated measures of 229 traits from targeted nuclear magnetic resonance (NMR) metabolomics. These traits included lipoprotein subclass-specific cholesterol and triglyceride content, amino and fatty acids, inflammatory glycoprotein acetyls, and others, and were measured in childhood (age 8y), adolescence (age 16y), young-adulthood (age 18y), and adulthood (age 25y). For replication, two-sample Mendelian randomization (MR) was conducted using summary data from genome-wide association studies of metabolic traits from NMR in an independent sample of adults (N range 13,476 to 24,925; mean (SD) age range 23.9y (2.1y) to 61.3y (2.9y)). Among ALSPAC participants (49.7% male), the prevalence of type 2 diabetes was very low across time points (< 5 cases when first assessed at age 16y; 7 cases (0.4%) when assessed at age 25y). At age 8y, type 2 diabetes liability (per SD-higher GRS) was associated with lower lipids in high-density lipoprotein (HDL) particle subtypes - e.g. -0.03 SD (95% CI = -0.06, -0.003; P = 0.03) for total lipids in very-large HDL. At age 16y, associations remained strongest with lower lipids in HDL and became stronger with pre-glycemic traits including citrate (-0.06 SD, 95% CI = -0.09, -0.02; P = 1.41x10-03) and with glycoprotein acetyls (0.05 SD, 95% CI = 0.01, 0.08; P = 0.01). At age 18y, associations were stronger with branched chain amino acids including valine (0.06 SD; 95% CI = 0.02, 0.09; P = 1.24x10-03), while at age 25y, associations had strengthened with VLDL lipids and remained consistent with previously altered traits including HDL lipids. Results of two-sample MR in an independent sample of adults indicated persistent patterns of effect of type 2 diabetes liability, with higher type 2 diabetes liability positively associated with VLDL lipids and branched chain amino acid levels, and inversely associated with HDL lipids - again for large and very large HDL particularly (-0.004 SD (95% CI = -0.007, -0.002; P = 8.45x10-04) per 1 log odds of type 2 diabetes for total lipids in large HDL). Study limitations include modest sample sizes for ALSPAC analyses and limited coverage of protein and hormonal traits; insulin was absent as it is not quantified by NMR and not consistently available at each time point. Analyses were restricted to white-Europeans which reduced confounding by population structure but limited inference to other ethnic groups.\n\nConclusionsOur results support perturbed HDL lipid metabolism as one of the earliest features of type 2 diabetes liability which precedes higher branched chain amino acid and inflammatory glycoprotein acetyl levels. This feature is apparent in childhood as early as age 8y, decades before the clinical onset of disease.\n\nAuthor summaryO_ST_ABSWhy was this study done?C_ST_ABSO_LIType 2 diabetes develops for many years before diagnosis. Clinical disease is characterised by numerous metabolic perturbations that are detectable in circulation, but which of these reflect the developmental stages of type 2 diabetes - as opposed to independent causes of type 2 diabetes or markers of other disease processes - is unknown. Revealing traits specific to type 2 diabetes development could inform the targeting of key pathways to prevent the clinical onset of disease and its complications.\nC_LIO_LIGenetic liability to type 2 diabetes is less prone to confounding than measured type 2 diabetes or blood glucose and may help reveal early perturbations in the blood that arise in response to type 2 diabetes liability itself.\nC_LI\n\nWhat did the researchers do and find?O_LIWe examined effects of genetic liability to adult type 2 diabetes, based on a genetic risk score including 162 variants, on detailed metabolic traits measured on the same individuals across four stages of early life - childhood (age 8y), adolescence (age 16y), young-adulthood (age 18y), and adulthood (age 25y).\nC_LIO_LIWe found that higher type 2 diabetes liability was associated most consistently across ages with lower lipid content in certain subtypes of HDL particles. Effects were more gradual on higher lipid content in VLDL particles and on higher branched chain amino acid and inflammatory glycoprotein acetyl levels.\nC_LI\n\nWhat do these findings mean?O_LISigns of type 2 diabetes liability are detectable in the blood in childhood, decades before the disease becomes noticeable. These signs, taken to reflect the early features of, or coincident with, disease, likely involve lower lipid content in HDL particles, followed by higher levels of branched chain amino acids and inflammation.\nC_LIO_LIGenetic risk scores for adult diseases can be integrated with metabolic measurements taken earlier in life to help to reveal the timing at which signs of disease liability become visible and the traits most central to its development.\nC_LI

genetics↗

bioRxiv2019

Genetic factors influencing a neurobiological substrate for psychiatric disorders

A retrospective meta-analysis of magnetic resonance imaging voxel-based morphometry studies proposed that reduced gray matter volumes in the dorsal anterior cingulate and the left and right anterior insular cortex - areas that constitute hub nodes of the salience network - represent a common substrate for major psychiatric disorders. Here, we investigated the hypothesis that the common substrate serves as an intermediate phenotype to detect genetic risk variants relevant for psychiatric disease. To this end, after a data reduction step, we conducted genome-wide association studies of a combined common substrate measure in four population-based cohorts (n=2,271), followed by meta-analysis and replication in a fifth cohort (n=865). After correction for covariates, the heritability of the common substrate was estimated at 0.50 (standard error 0.18). The top single-nucleotide polymorphism (SNP) rs17076061 was associated with the common substrate at genome-wide significance and replicated, explaining 1.2% of the common substrate variance. This SNP mapped to a locus on chromosome 5q35.2 harboring genes involved in neuronal development and regeneration. In follow-up analyses, rs17076061 was not robustly associated with psychiatric disease, and no overlap was found between the broader genetic architecture of the common substrate and genetic risk for major depressive disorder, bipolar disorder, or schizophrenia. In conclusion, our study identified that common genetic variation indeed influences the common substrate, but that these variants do not directly translate to increased disease risk. Future studies should investigate gene-by-environment interactions and employ functional imaging to understand how salience network structure translates to psychiatric disorder risk.

genetics↗

bioRxiv2019

The genetics of male pheromone preference difference between Drosophila melanogaster and D. simulans

Species of flies in the genus Drosophila differ dramatically in their preferences for mates, but little is known about the genetic or neurological underpinnings of this evolution. Recent advances have been made to our understanding of one case: pheromone preference evolution between the species D. melanogaster and D. simulans. Males of both species are very sensitive to the pheromone 7,11-HD that is present only on the cuticle of female D. melanogaster. In one species this cue activates courtship, and in the other it represses it. This change in valence was recently shown to result from the modification of central processing neurons, rather than changes in peripherally expressed receptors, but nothing is known about the genetic changes that are responsible. In the current study, we show that a 1.35 Mb locus on the X chromosome has a major effect on male 7,11-HD preference. Unfortunately, when this locus is divided, the effect is largely lost. We instead attempt to filter the 159 genes within this region using our newfound understanding of the neuronal underpinnings of this phenotype to identify and test candidate genes. We present the results of these tests, and discuss the difficulty of identifying the genetic architecture of behavioral traits and the potential of connecting these genetic changes to the neuronal modifications that elicit different behaviors.

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bioRxiv2019

A Genotype Concordance Study between Consumer Genetic Testing Services

The consumer genomics industry is steadily growing and delivering genetic information to over 10 million individuals. Yet, the implications of using data from different services remain unclear. We investigated the genotyped sites, concordance, and genetic risk estimation using data from three major consumer services. We found low overlap among reported genotyped sites (2.7% across all three). While there was a high concordance between overlapping sites of the two SNP-array services (99.6%), there was a lower concordance between them and a low-pass whole-genome service (73.0%). Finally, we demonstrated that the discrepancy resulted in distinct APOE genotypes and genetic risk scores of Alzheimers disease determined using these data. Our results demonstrate genotype results across consumer genomics platforms may lead to different genetic risk estimates, highlighting the need for careful quality control and interpretation.

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bioRxiv2019

Genetic and clinical analyses of psychosis spectrum symptoms in a large multi-ethnic youth cohort reveal significant link with ADHD.

ObjectivePsychotic symptoms are an important feature of severe neuropsychiatric disorders, but are also common in the general population, especially in youth. The genetic etiology of psychosis symptoms in youth remains poorly understood. To characterize genetic risk for psychosis spectrum symptoms (PS), we leverage a community-based multi-ethnic sample of children and adolescents aged 8-22 years, the Philadelphia Neurodevelopmental Cohort (n = 7,225, 20% PS).\n\nMethodsUsing an elastic net regression model, we aim to classify PS status using polygenic scores (PGS) based on a range of heritable psychiatric and brain-related traits in a multi-PGS model. We also perform univariate PGS associations and evaluate age-specific effects.\n\nResultsThe multi-PGS analyses do not improve prediction of PS status over univariate models, but reveal that the attention deficit hyperactivity disorder (ADHD) PGS is robustly and uniquely associated with PS (OR 1.12 (1.05, 1.18) P = 0.0003). This association is: i) driven by subjects of European ancestry (OR=1.23 (1.14, 1.34), P=4.15x10-7) but is not observed in African American subjects (P=0.65) and ii) independent of phenotypic overlap. We also find a significant interaction with age (P=0.01), with a stronger association in younger children. In an independent sample, we replicate an increased ADHD PGS in 328 youth at clinical high risk for psychosis, compared to 216 unaffected controls (OR 1.06, CI(1.01, 1.11), P= 0.02).\n\nConclusionsOur findings suggest that PS in youth may reflect a different genetic etiology than psychotic symptoms in adulthood, one more akin to ADHD, and shed light on how genetic risk can be investigated across early disease trajectories.

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bioRxiv2019

Using genetics to disentangle the complex relationship between food choices and health status

Despite food choices being one of the most important factors influencing health, efforts to identify individual food groups and dietary patterns that cause disease have been challenging, with traditional nutritional epidemiological approaches plagued by biases and confounding. After identifying 302 individual genetic determinants of dietary intake in 445,779 individuals in the UK Biobank study, we develop a statistical genetics framework that enables us, to directly assess the impact of food choices on health outcomes. We show that the biases which affect observational studies extend also to GWAS, genetic correlations and causal inference through genetics, which can be corrected by applying our methods. Finally, by applying Mendelian Randomization approaches to the corrected results we identify some of the first robust causal associations between eating patterns and cancer, heart disease, obesity, and several other health related risk factors, distinguishing between the effects of specific foods or dietary patterns.

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