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bioRxiv2026

Dissecting the genetic basis of DUS characters in Pakistani wheat varieties

Distinctness, Uniformity and Stability (DUS) testing is fundamental to varietal characterization and the protection of Plant Breeders Rights (PBRs), but conventional DUS assessment relies predominantly on morphological characteristics whose expression may be influenced by environmental conditions, developmental stage and observer-related variation. Integrating character-specific molecular markers with conventional DUS assessment may therefore improve the reproducibility and genetic resolution of varietal identification. This study investigated the genetic architecture of DUS characteristics in a panel of 102 historical and modern Pakistani wheat varieties using genome-wide association studies (GWAS). Phenotypic variation was evaluated using distribution, correlation and hierarchical clustering analyses, while the germplasm was genotyped using a wheat genotyping-by-targeted sequencing platform. After quality filtering, 21,670 high-quality single-nucleotide polymorphisms (SNPs) were retained for analyses of genetic diversity, population structure, linkage disequilibrium (LD) and marker-trait associations. Population structure analysis indicated extensive admixture, with cross-entropy supporting K = 9 ancestral components, whereas hierarchical genetic clustering separated the germplasm into five broad groups. The first three principal components explained 8.09%, 7.20% and 5.39% of the total genetic variation, respectively. GWAS using BLINK and FarmCPU identified significant associations for several diagnostically important DUS characteristics. Growth habit was strongly associated with SNP 1B_129176704, with an additional signal on chromosome 5B. Shattering showed its strongest association at 1D_445256324, accompanied by several closely linked SNPs in the same region and a secondary significant locus at 7B_703502819. Flag leaf length was associated with a cluster of SNPs on chromosome 6A, while tiller density showed a major association with 5D_205488820. These findings demonstrate substantial phenotypic and genetic diversity within Pakistani wheat germplasm and identify genomic regions that merit validation as character-specific molecular tools to complement conventional DUS testing and PBR implementation.

plant biology↗

bioRxiv2016

Transethnic genetic correlation estimates from summary statistics

The increasing number of genetic association studies conducted in multiple populations provides unprecedented opportunity to study how the genetic architecture of complex phenotypes varies between populations, a problem important for both medical and population genetics. Here we develop a method for estimating the transethnic genetic correlation: the correlation of causal variant effect sizes at SNPs common in populations. We take advantage of the entire spectrum of SNP associations and use only summary-level GWAS data. This avoids the computational costs and privacy concerns associated with genotype-level information while remaining scalable to hundreds of thousands of individuals and millions of SNPs. We apply our method to gene expression, rheumatoid arthritis, and type-two diabetes data and overwhelmingly find that the genetic correlation is significantly less than 1. Our method is implemented in a python package called popcorn.

Genetics↗

bioRxiv2016

Implementing rapid, robust, cost-effective, patient-centred, routine genetic testing in ovarian cancer patients

BackgroundAdvances in DNA sequencing have made gene testing fast and affordable, but adaptation of clinical services to capitalise on this for patient benefit has been slow. Ovarian cancer exemplifies limitations of current systems and potential benefits of increased gene testing. Approximately 15% of ovarian cancer patients have a germline mutation in BRCA1 or BRCA2 (collectively termed BRCA) and this has substantial implications for their personal management and that of their relatives. However, in most countries implementation of BRCA testing in ovarian cancer has been inconsistent and largely unsuccessful.\n\nMethodsWe developed a mainstream pathway in which BRCA testing was undertaken by cancer team members after 30 minutes online training. Patients with a mutation were sent a genetic appointment with their results. Cascade testing to relatives was performed via standard clinical genetic procedures.\n\nFindings207 women with ovarian cancer were offered gene testing through the mainstream pathway and all accepted. 33 (16%) had a BRCA mutation. The result informed management of 79% (121/154) women with active disease including 97% (32/33) women with a mutation. All mutation-positive women and ~3.5 relatives per family have been seen in genetics. Patient and clinician feedback was very positive. >95% found the pathway to be simple and effective. The pathway offers considerable reduction in time (~5-fold) and resource requirements (~13-fold) compared to the traditional genetic pathway. We estimate it would deliver {pound}2.6M NHS cost savings per year, and would allow implementation of national testing recommendations with existing infrastructure.\n\nInterpretationMainstream genetic testing is effective, efficient and patient-centred and offers a mechanism for large-scale implementation of BRCA gene testing in cancer patients. The principles could be applied in many other countries and to many other areas of genomic medicine.

Genetics↗

bioRxiv2016

Insights into the genetic epidemiology of Crohn’s and rare diseases in the Ashkenazi Jewish population

As part of a broader collaborative network of exome sequencing studies, we developed a jointly called data set of 5,685 Ashkenazi Jewish exomes. We make publicly available a resource of site and allele frequencies, which should serve as a reference for medical genetics in the Ashkenazim. We estimate that 30% of protein-coding alleles present in the Ashkenazi Jewish population at frequencies greater than 0.2% are significantly more frequent (mean 7.6-fold) than their maximum frequency observed in other reference populations. Arising via a well-described founder effect, this catalog of enriched alleles can contribute to differences in genetic risk and overall prevalence of diseases between populations. As validation we document 151 AJ enriched protein-altering alleles that overlap with \"pathogenic\" ClinVar alleles, including those that account for 10-100 fold differences in prevalence between AJ and non-AJ populations of some rare diseases including Gaucher disease (GBA, p.Asn409Ser, 8-fold enrichment); Canavan disease (ASPA, p.Glu285Ala, 12-fold enrichment); and Tay-Sachs disease (HEXA, c.1421+1G>C, 27-fold enrichment; p.Tyr427IlefsTer5, 12-fold enrichment). We next sought to use this catalog, of well-established relevance to Mendelian disease, to explore Crohns disease, a common disease with an estimated two to four-fold excess prevalence in AJ. We specifically evaluate whether strong acting rare alleles, enriched by the same founder-effect, contribute excess genetic risk to Crohns disease in AJ, and find that ten rare genetic risk factors in NOD2 and LRRK2 are strongly enriched in AJ, including several novel contributing alleles, show evidence of association to CD. Independently, we find that genomewide common variant risk defined by GWAS shows a strong difference between AJ and non-AJ European control population samples (0.97 s.d. higher, p<10-16). Taken together, the results suggest coordinated selection in AJ population for higher CD risk alleles in general. The results and approach illustrate the value of exome sequencing data in case-control studies along with reference data sets like ExAC to pinpoint genetic variation that contributes to variable disease predisposition across populations.

Genetics↗

bioRxiv2020

Genetic Variants and Functional Pathways Associated with Resilience to Alzheimer's Disease

Approximately 30% of older adults exhibit the neuropathologic features of Alzheimers disease (AD) without signs of cognitive impairment. Yet, little is known about the genetic factors that allow these potentially resilient individuals to remain cognitively normal in the face of substantial neuropathology. We performed a large, genome-wide association study (GWAS) of two previously validated metrics of cognitive resilience quantified using a latent variable modeling approach and representing better-than-predicted cognitive performance for a given level of neuropathology. Data were harmonized across 5,108 participants from a clinical trial of AD and three longitudinal cohort studies of cognitive aging. All analyses were run across all participants and repeated restricting the sample to individuals with normal cognition to identify variants at the earliest stages of disease. As expected, all resilience metrics were genetically correlated with cognitive performance and education attainment traits (p-values<2.5x10-20), and we observed novel correlations with neuropsychiatric conditions (p-values<7.9x10-4). Notably, neither resilience metric was genetically correlated with clinical AD (p-values>0.42) nor associated with APOE (p-values>0.13). In single variant analyses, we observed a genome-wide significant locus among participants with normal cognition on chromosome 18 upstream of ATP8B1 (index SNP rs2571244, MAF=0.08, p=2.3x10-8). The top variant at this locus (rs2571244) was significantly associated with methylation in prefrontal cortex tissue at multiple CpG sites, including one just upstream of ATPB81 (cg19596477; p=2x10-13). Overall, this comprehensive genetic analysis of resilience implicates a putative role of vascular risk, metabolism, and mental health in protection from the cognitive consequences of neuropathology, while also providing evidence for a novel resilience gene along the bile acid metabolism pathway. Furthermore, the genetic architecture of resilience appears to be distinct from that of clinical AD, suggesting that a shift in focus to molecular contributors to resilience may identify novel pathways for therapeutic targets.

genetics↗

bioRxiv2021

Manifestations of genetic risk for Alzheimer's Disease in the blood: a cross-sectional multi-omic analysis in healthy adults aged 18-90+

Deeply phenotyped cohort data can elucidate differences associated with genetic risk for common complex diseases across an age spectrum. Previous work has identified genetic variants associated with Alzheimers disease (AD) risk from large-scale genome-wide association study meta-analyses. To explore effects of known AD-risk variants, we performed a phenome-wide association study on ~2000 clinical, proteomic, and metabolic blood-based analytes obtained from 2,831 cognitively normal adult clients of a consumer-based scientific wellness company. Results uncovered statistically significant SNP-analyte associations for five genetic variants after correction for multiple testing (for SNPs in or near NYAP1, ABCA7, INPP5D, and APOE). These effects were detectable from early adulthood. Sex modified the effects of four genetic variants, with multiple interrelated immune-modulating effects associated with the PICALM variant. Sex-stratified GWAS results from an independent AD case-control meta-analysis supported sexspecific disease effects of the PICALM variant, highlighting the importance of sex as a biological variable. These analyses support evidence from previous functional genomics studies in the identification of a causal variant within the PILRA gene. Taken together, this study highlights clues to the earliest effects of AD genetic risk variants in individuals where disease symptoms have not (yet) arisen.

genetics↗

bioRxiv2014

Tracing the genetic origin of Europe’s first farmers reveals insights into their social organization

Farming was established in Central Europe by the Linearbandkeramik culture (LBK), a well-investigated archaeological horizon, which emerged in the Carpathian Basin, in today's Hungary. However, the genetic background of the LBK genesis has not been revealed yet. Here we present 9 Y chromosomal and 84 mitochondrial DNA profiles from Mesolithic, Neolithic Starevo and LBK sites (7th/6th millennium BC) from the Carpathian Basin and south-eastern Europe. We detect genetic continuity of both maternal and paternal elements during the initial spread of agriculture, and confirm the substantial genetic impact of early farming south-eastern European and Carpathian Basin cultures on Central European populations of the 6th-4th millennium BC. Our comprehensive Y chromosomal and mitochondrial DNA population genetic analyses demonstrate a clear affinity of the early farmers to the modern Near East and Caucasus, tracing the expansion from that region through south-eastern Europe and the Carpathian Basin into Central Europe. Our results also reveal contrasting patterns for male and female genetic diversity in the European Neolithic, suggesting patrilineal descent system and patrilocal residential rules among the early farmers.

Genetics↗

bioRxiv2014

Behavioral individuality reveals genetic control of phenotypic variability

Variability is ubiquitous in nature and a fundamental feature of complex systems. Few studies, however, have investigated variance itself as a trait under genetic control. By focusing primarily on trait means and ignoring the effect of alternative alleles on trait variability, we may be missing an important axis of genetic variation contributing to phenotypic differences among individuals1,2. To study genetic effects on individual-to-individual phenotypic variability (or intragenotypic variability), we used a panel of Drosophila inbred lines3 and focused on locomotor handedness4, in an assay optimized to measure variability. We discovered that some lines had consistently high levels of intragenotypic variability among individuals while others had low levels. We demonstrate that the degree of variability is itself heritable. Using a genome-wide association study (GWAS) for the degree of intragenotypic variability as the phenotype across lines, we identified several genes expressed in the brain that affect variability in handedness without affecting the mean. One of these genes, Ten-a, implicated a neuropil in the central complex5 of the fly brain as influencing the magnitude of behavioral variability, a brain region involved in sensory integration and locomotor coordination6. We have validated these results using genetic deficiencies, null alleles, and inducible RNAi transgenes. This study reveals the constellation of phenotypes that can arise from a single genotype and it shows that different genetic backgrounds differ dramatically in their propensity for phenotypic variability. Because traditional mean-focused GWASs ignore the contribution of variability to overall phenotypic variation, current methods may miss important links between genotype and phenotype.\n\nAbbreviationsDGRP: Drosophila Genome Reference Panel; ANOMV: Analysis of means for variance; QTL: quantitative trait loci, GWAS: genome wide association study, MAD: median absolute deviation. GWAS: genome wide association study, CI: confidence interval.

Genetics↗

bioRxiv2014

The genetic architecture of neurodevelopmental disorders

Neurodevelopmental disorders include rare conditions caused by identified single mutations, such as Fragile X, Down and Angelman syndromes, and much more common clinical categories such as autism, epilepsy and schizophrenia. These common conditions are all highly heritable but their genetics is considered to be \"complex\". In fact, this sharp dichotomy in genetic architecture between rare and common disorders may be largely artificial. On the one hand, much of the apparent complexity in the genetics of common disorders may derive from underlying genetic heterogeneity, which has remained obscure until recently. On the other hand, even for supposedly Mendelian conditions, the relationship between single mutations and clinical phenotypes is rarely simple. The categories of monogenic and complex disorders may therefore merge across a continuum, with some mutations being strongly associated with specific syndromes and others having a more variable outcome, modified by the presence of additional genetic variants.

Genetics↗

bioRxiv2014

Genetic Analysis of Substrain Divergence in NOD Mice

ABSTRACTThe NOD mouse is a polygenic model for type 1 diabetes that is characterized by insulitis, a leukocytic infiltration of the pancreatic islets. During ~35 years since the original inbred strain was developed in Japan, NOD substrains have been established at different laboratories around the world. Although environmental differences among NOD colonies capable of impacting diabetes incidence have been recognized, differences arising from genetic divergence have not previously been analyzed. We use both Mouse Diversity Array and Whole Exome Capture Sequencing platforms to identify genetic differences distinguishing 5 NOD substrains. We describe 64 SNPs, and 2 short indels that differ in coding regions of the 5 NOD substrains. A 100 kb deletion on Chromosome 3 distinguishes NOD/ShiLtJ and NOD/ShiLtDvs from 3 other substrains, while a 111 kb deletion in the Icam2 gene on Chromosome 11 is unique to the NOD/ShiLtDvs genome. The extent of genetic divergence for NOD substrains is compared to similar studies for C57BL6 and BALB/c substrains. As mutations are fixed to homozygosity by continued inbreeding, significant differences in substrain phenotypes are to be expected. These results emphasize the importance of using embryo freezing methods to minimize genetic drift within substrains and of applying appropriate genetic nomenclature to permit substrain recognition when one is used.

Genetics↗

bioRxiv2014

Scaling probabilistic models of genetic variation to millions of humans

One of the major goals of population genetics is to quantitatively understand variation of genetic polymorphisms among individuals. To this end, researchers have developed sophisticated statistical methods to capture the complex population structure that underlies observed genotypes in humans, and such methods have been effective for analyzing modestly sized genomic data sets. However, the number of genotyped humans has grown significantly in recent years, and it is accelerating. In aggregate about 1M individuals have been genotyped to date. Analyzing these data will bring us closer to a nearly complete picture of human genetic variation; but existing methods for population genetics analysis do not scale to data of this size. To solve this problem we developed TeraStructure. TeraStructure is a new algorithm to fit Bayesian models of genetic variation in human populations on tera-sample-sized data sets (1012 observed genotypes, e.g., 1M individuals at 1M SNPs). It is a principled approach to Bayesian inference that iterates between subsampling locations of the genome and updating an estimate of the latent population structure of the individuals. On data sets of up to 2K individuals, TeraStructure matches the existing state of the art in terms of both speed and accuracy. On simulated data sets of up to 10K individuals, TeraStructure is twice as fast as existing methods and has higher accuracy in recovering the latent population structure. On genomic data simulated at the tera-sample-size scales, TeraStructure continues to be accurate and is the only method that can complete its analysis.\n\nSoftwareTeraStructure is available for download at https://github.com/premgopalan/terastructure.\n\nFundingThis research was supported in part by NIH grant R01 HG006448 and ONR grant N00014-12-1-0764.

Genetics↗

bioRxiv2015

Genetics of intra-species variation in avoidance behavior induced by a thermal stimulus in C. elegans

Individuals within a species vary in their responses to a wide range of stimuli, partly as a result of differences in their genetic makeup. Relatively little is known about the genetic and neuronal mechanisms contributing to diversity of behavior in natural populations. By studying animal-to-animal variation in innate avoidance behavior to thermal stimuli in the nematode Caenorhabditis elegans, we uncovered genetic principles of how different components of a behavioral response can be altered in nature to generate behavioral diversity. Using a thermal pulse assay, we uncovered heritable variation in responses to a transient temperature increase. Quantitative trait locus mapping revealed that separate components of this response were controlled by distinct genomic loci. The loci we identified contributed to variation in components of thermal pulse avoidance behavior in an additive fashion. Our results show that the escape behavior induced by thermal stimuli is composed of simpler behavioral components that are influenced by at least six distinct genetic loci. The loci that decouple components of the escape behavior reveal a genetic system that allows independent modification of behavioral parameters. Our work sets the foundation for future studies of evolution of innate behaviors at the molecular and neuronal level.

Genetics↗

bioRxiv2015

An Atlas of Genetic Correlations across Human Diseases and Traits

Identifying genetic correlations between complex traits and diseases can provide useful etiological insights and help prioritize likely causal relationships. The major challenges preventing estimation of genetic correlation from genome-wide association study (GWAS) data with current methods are the lack of availability of individual genotype data and widespread sample overlap among meta-analyses. We circumvent these difficulties by introducing a technique for estimating genetic correlation that requires only GWAS summary statistics and is not biased by sample overlap. We use our method to estimate 300 genetic correlations among 25 traits, totaling more than 1.5 million unique phenotype measurements. Our results include genetic correlations between anorexia nervosa and schizophrenia, anorexia and obesity and associations between educational attainment and several diseases. These results highlight the power of genome-wide analyses, since there currently are no genome-wide significant SNPs for anorexia nervosa and only three for educational attainment.

Genomics↗

bioRxiv2015

The genetics of Bene Israel from India reveals both substantial Jewish and Indian ancestry

The Bene Israel Jewish community from West India is a unique population whose history before the 18th century remains largely unknown. Bene Israel members consider themselves as descendants of Jews, yet the identity of Jewish ancestors and their arrival time to India are unknown, with speculations on arrival time varying between the 8th century BCE and the 6th century CE. Here, we characterize the genetic history of Bene Israel by collecting and genotyping 18 Bene Israel individuals. Combining with 486 individuals from 41 other Jewish, Indian and Pakistani populations, and additional individuals from worldwide populations, we conducted comprehensive genome-wide analyses based on FST, principal component analysis, ADMIXTURE, identity-by-descent sharing, admixture linkage disequilibrium decay, haplotype sharing and allele sharing autocorrelation decay, as well as contrasted patterns between the X chromosome and the autosomes. The genetics of Bene Israel individuals resemble local Indian populations, while at the same time constituting a clearly separated and unique population in India. They are unique among Indian and Pakistani populations we analyzed in sharing considerable genetic ancestry with other Jewish populations. Putting together the results from all analyses point to Bene Israel being an admixed population with both Jewish and Indian ancestry, with the genetic contribution of each of these ancestral populations being substantial. The admixture took place in the last millennium, about 19-33 generations ago. It involved Middle-Eastern Jews and was sex-biased, with more male Jewish and local female contribution. It was followed by a population bottleneck and high endogamy, which can lead to increased prevalence of recessive diseases in this population. This study provides an example of how genetic analysis advances our knowledge of human history in cases where other disciplines lack the relevant data to do so.

Genetics↗

bioRxiv2016

Differential methylation between ethnic sub-groups reflects the effect of genetic ancestry and environmental exposures

In clinical practice and biomedical research populations are often divided categorically into distinct racial/ethnic groups. In reality, these categories, which are based on social rather than biological constructs, comprise diverse groups with highly heterogeneous histories, cultures, traditions, religions, social and environmental exposures and ancestral backgrounds. Their use is thus widely debated and genetic ancestry has been suggested as a complement or alternative to this categorization. However, few studies have examined the relative contributions of racial/ethnic identity, genetic ancestry, and environmental exposures on well-established and fundamental biological processes. We examined the associations between ethnicity, ancestry, and environmental exposures and DNA methylation. We typed over 450,000 CpG sites in primary whole blood of 573 individuals of diverse Hispanic descent who also had high-density genotype data. We found that both self-identified ethnicity and genetically determined ancestry were significantly associated with methylation levels at a large number of CpG sites (916 and 194, respectively). Among loci differentially methylated between ethnic groups, a median of 75.7% (IQR 45.8% to 92%) of the variance in methylation associated with ethnicity could be accounted for by shared genomic ancestry accounts. We also found significant enrichment (p = 4.2 x 10-64) of ethnicity-associated sites amongst loci previously associated with environmental and social exposures, particularly maternal smoking during pregnancy. Our study suggests that although differential methylation between ethnic groups can be partially explained by the shared genetic ancestry, a significant effect of ethnicity is likely due to environmental, social, or cultural factors, which differ between ethnic groups.\n\nOne Sentence SummaryIn order to better understand the role of ethnic self-identification and genetically determined ancestry in biomedical outcomes, we explore their relative contributions to variation in methylation, a fundamental biological process.\n\nSources of FundingThis research was supported in part by the Sandler Family Foundation, the American Asthma Foundation, National Institutes of Health (P60 MD006902, R01 HL117004, R21ES24844, U54MD009523, R01 ES015794, R01 HL088133, M01 RR000083, R01 HL078885, R01 HL104608, U19 AI077439, M01 RR00188, U01 HG009080, and R01 HL135156), ARRA grant RC2 HL101651, and TRDRP 24RT-0025; EGB was supported in part through grants from the Flight Attendant Medical Research Institute (FAMRI), and NIH (K23 HL004464); NZ was supported in part by an NIH career development award from the NHLBI (K25HL121295). JMG was supported in part by NIH Training Grant T32 (T32GM007546) and career development awards from the NHLBI (K23HL111636) and NCATS (KL2TR000143) as well as the Hewett Fellowship; N.T. was supported in part by an institutional training grant from the NIGMS (T32-GM007546) and career development awards from the NHLBI (K12-HL119997 and K23-HL125551), Parker B. Francis Fellowship Program, and the American Thoracic Society; CRG was supported in part by NIH Training Grant T32 (GM007175) and the UCSF Chancellors Research Fellowship and Dissertation Year Fellowship; RK was supported with a career development award from the NHLBI (K23HL093023); HJF was supported in part by the GCRC (RR00188); PCA was supported in part by the Ernest S. Bazley Grant; MAS was supported in part by 1R01HL128439-01. This publication was supported by various institutes within the National Institutes of Health. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIH.

Genetics↗

bioRxiv2016

Genetic Influences on Hormonal Markers of Chronic HPA Function in Human Hair

Cortisol is the primary output of the hypothalamic-pituitary-adrenal (HPA) axis and is central to the human biological stress response, with wide-ranging effects on physiological function and psychiatric health. In both humans and animals, cortisol is frequently studied as a biomarker for exposure to environmental stress. Relatively little attention has been paid to the possible role of genetic variation in heterogeneity in chronic cortisol, in spite of well-studied biological pathways of glucocorticoid function. Using recently developed technology, hair samples can now be used to measure accumulation of cortisol over several months. In contrast to more conventional salivary measures, hair cortisol is not influenced by diurnal variation or transient hormonal reactivity. In an ethnically and socioeconomically diverse sample of 1 070 child and adolescent twins and multiples from 556 unique families, we estimated genetic and environmental influences on hair concentrations of cortisol and its inactive metabolite, cortisone. We identified sizable genetic influences on cortisol that decrease with age, concomitant with genetic influences on cortisone that increase with age. Shared environmental influences on cortisol and cortisone were modest and, for cortisol, decreased with age. Twin-specific, non-shared environmental contributions to cortisol and cortisone became increasingly correlated with age. We find some evidence for sex differences in the biometric contributions to cortisol, but no strong evidence for main or moderating effects of family socioeconomic status on cortisol or cortisone. This study constitutes the first genetic study of hormone concentrations in human hair, and provides the most definitive characterization to-date of age and socioeconomic influences on hair cortisol.

Genetics↗

bioRxiv2016

Maternal Genetic Ancestry and Legacy of 10th Century AD Hungarians

The ancient Hungarians originated from the Ural region in todays central Russia and migrated across the Eastern European steppe, according to historical sources. The Hungarians conquered the Carpathian Basin 895-907 AD, and admixed with the indigenous communities.\n\nHere we present mitochondrial DNA results from three datasets: one from the Avar period (7th -9th centuries) of the Carpathian Basin (n = 31); one from the Hungarian conquest-period (n=76); and a completion of the published 10th-12th century Hungarian-Slavic contact zone dataset by four samples. We compare these mitochondrial DNA hypervariable segment sequences and haplogroup results with published ancient and modern Eurasian data. Whereas the analyzed Avars represents a certain group of the Avar society that shows East and South European genetic characteristics, the Hungarian conquerors maternal gene pool is a mixture of West Eurasian and Central and North Eurasian elements. Comprehensively analyzing the results, both the linguistically recorded Finno-Ugric roots and historically documented Turkic and Central Asian influxes had possible genetic imprints in the conquerors genetic composition. Our data allows a complex series of historic and population genetic events before the formation of the medieval population of the Carpathian Basin, and the maternal genetic continuity between 10th- 12th century and modern Hungarians.

Genetics↗

bioRxiv2016

Do Regional Brain Volumes and Major Depressive Disorder Share Genetic Architecture: a study in Generation Scotland (n=19,762), UK Biobank (n=24,048) and the English Longitudinal Study of Ageing (n=5,766)

Major depressive disorder (MDD) is a heritable and highly debilitating condition. It is commonly associated with subcortical volumetric abnormalities, the most replicated of these being reduced hippocampal volume. Using the most recent published data from ENIGMA consortiums genome-wide association study (GWAS) of regional brain volume, we sought to test whether there is shared genetic architecture between 8 subcortical brain volumes and MDD. Using LD score regression utilising summary statistics from ENIGMA and the Psychiatric Genomics Consortium, we demonstrated that hippocampal volume was positively genetically correlated with MDD (rG=0.46, P=0.02), although this did not survive multiple comparison testing. None of other six brain regions studied were genetically correlated and amygdala volume heritability was too low for analysis. We also generated polygenic risk scores (PRS) to assess potential pleiotropy between regional brain volumes and MDD in three cohorts (Generation Scotland; Scottish Family Health Study (n=19,762), UK Biobank (n=24,048) and the English Longitudinal Study of Ageing (n=5,766). We used logistic regression to examine volumetric PRS and MDD and performed a meta-analysis across the three cohorts. No regional volumetric PRS demonstrated significant association with MDD or recurrent MDD. In this study we provide some evidence that hippocampal volume and MDD may share genetic architecture, albeit this did not survive multiple testing correction and was in the opposite direction to most reported phenotypic correlations. We therefore found no evidence to support a shared genetic architecture for MDD and regional subcortical volumes.

Genetics↗