A new common functional coding variant at the DDC gene change renal enzyme activity and modify renal dopamine function.

The intra-renal dopamine (DA) system is highly expressed in the proximal tubule and contributes to Na+ and blood pressure homeostasis, as well as to the development of nephropathy. In the kidney, the enzyme DOPA Decarboxylase (DDC) originating from the circulation. We used a twin/family study design, followed by polymorphism association analysis at DDC locus to elucidate heritable influences on renal DA production. Dense single nucleotide polymorphism (SNP) genotyping across the DDC locus on chromosome 7p12 was analyzed by re-sequencing guided by trait-associated genetic markers to discover the responsible genetic variation. We also characterized kinetics of the expressed DDC mutant enzyme. Systematic polymorphism screening across the 15-Exon DDC locus revealed a single coding variant in Exon-14 that was associated with DA excretion and multiple other renal traits indicating pleiotropy. When expressed and characterized in eukaryotic cells, the 462Gln variant displayed lower Vmax (maximal rate of product formation by an enzyme) (21.3 versus 44.9 nmol/min/mg) and lower Km (substrate concentration at which half-maximal product formation is achieved by an enzyme.)(36.2 versus 46.8 μM) than the wild-type (Arg462) allele. The highly heritable DA excretion trait is substantially influenced by a previously uncharacterized common coding variant (Arg462Gln) at the DDC gene that affects multiple renal tubular and glomerular traits, and predicts accelerated functional decline in chronic kidney disease

Use of Cholecystokinin to Prevent the Development of Parenteral Nutritionâ Associated Cholestasis

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142290/1/jpen0100.pd

Genetic Implication of a Novel Thiamine Transporter in Human Hypertension

ObjectivesThis study coupled 2 strategies—trait extremes and genome-wide pooling—to discover a novel blood pressure (BP) locus that encodes a previously uncharacterized thiamine transporter.BackgroundHypertension is a heritable trait that remains the most potent and widespread cardiovascular risk factor, although details of its genetic determination are poorly understood.MethodsRepresentative genomic deoxyribonucleic acid (DNA) pools were created from male and female subjects in the highest- and lowest-fifth percentiles of BP in a primary care population of >50,000 patients. The peak associated single-nucleotide polymorphisms were typed in individual DNA samples, as well as in twins/siblings phenotyped for cardiovascular and autonomic traits. Biochemical properties of the associated transporter were evaluated in cellular assays.ResultsAfter chip hybridization and calculation of relative allele scores, the peak associations were typed in individual samples, revealing an association between hypertension, systolic BP, and diastolic BP and the previously uncharacterized solute carrier SLC35F3. The BP genetic association at SLC35F3 was validated by meta-analysis in an independent sample from the original source population, as well as the International Consortium for Blood Pressure Genome-Wide Association Studies (across North America and western Europe). Sequence homology to a putative yeast thiamine (vitamin B1) transporter prompted us to express human SLC35F3 in Escherichia coli, which catalyzed [3H]-thiamine uptake. SLC35F3 risk-allele homozygotes (T/T) displayed decreased erythrocyte thiamine content on microbiological assay. In twin pairs, the SLC35F3 risk allele predicted heritable cardiovascular traits previously associated with thiamine deficiency, including elevated cardiac stroke volume with decreased vascular resistance, and elevated pressor responses to environmental (cold) stress. Allelic expression imbalance confirmed that cis variation at the human SLC35F3 locus influenced expression of that gene, and the allelic expression imbalance peak coincided with the hypertension peak.ConclusionsNovel strategies were coupled to position a new hypertension-susceptibility locus, uncovering a previously unsuspected thiamine transporter whose genetic variants predicted several disturbances in cardiac and autonomic function. The results have implications for the pathogenesis and treatment of systemic hypertension

Leveraging genomic annotations and pleiotropic enrichment for improved replication rates in schizophrenia GWAS

Most of the genetic architecture of schizophrenia (SCZ) has not yet been identified. Here, we apply a novel statistical algorithm called Covariate-Modulated Mixture Modeling (CM3), which incorporates auxiliary information (heterozygosity, total linkage disequilibrium, genomic annotations, pleiotropy) for each single nucleotide polymorphism (SNP) to enable more accurate estimation of replication probabilities, conditional on the observed test statistic (“z-score”) of the SNP. We use a multiple logistic regression on z-scores to combine information from auxiliary information to derive a “relative enrichment score” for each SNP. For each stratum of these relative enrichment scores, we obtain nonparametric estimates of posterior expected test statistics and replication probabilities as a function of discovery z-scores, using a resampling-based approach that repeatedly and randomly partitions meta-analysis sub-studies into training and replication samples. We fit a scale mixture of two Gaussians model to each stratum, obtaining parameter estimates that minimize the sum of squared differences of the scale-mixture model with the stratified nonparametric estimates. We apply this approach to the recent genome-wide association study (GWAS) of SCZ (n = 82,315), obtaining a good fit between the model-based and observed effect sizes and replication probabilities. We observed that SNPs with low enrichment scores replicate with a lower probability than SNPs with high enrichment scores even when both they are genome-wide significant (p < 5x10-8). There were 693 and 219 independent loci with model-based replication rates ≥80% and ≥90%, respectively. Compared to analyses not incorporating relative enrichment scores, CM3 increased out-of-sample yield for SNPs that replicate at a given rate. This demonstrates that replication probabilities can be more accurately estimated using prior enrichment information with CM3

Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders

Personality is influenced by genetic and environmental factors1 and associated with mental health. However, the underlying genetic determinants are largely unknown. We identified six genetic loci, including five novel loci2,3, significantly associated with personality traits in a meta-analysis of genome-wide association studies (N = 123,132–260,861). Of these genomewide significant loci, extraversion was associated with variants in WSCD2 and near PCDH15, and neuroticism with variants on chromosome 8p23.1 and in L3MBTL2. We performed a principal component analysis to extract major dimensions underlying genetic variations among five personality traits and six psychiatric disorders (N = 5,422–18,759). The first genetic dimension separated personality traits and psychiatric disorders, except that neuroticism and openness to experience were clustered with the disorders. High genetic correlations were found between extraversion and attention-deficit– hyperactivity disorder (ADHD) and between openness and schizophrenia and bipolar disorder. The second genetic dimension was closely aligned with extraversion–introversion and grouped neuroticism with internalizing psychopathology (e.g., depression or anxiety)

The selection landscape and genetic legacy of ancient Eurasians

The Holocene (beginning around 12,000 years ago) encompassed some of the most significant changes in human evolution, with far-reaching consequences for the dietary, physical and mental health of present-day populations. Using a dataset of more than 1,600 imputed ancient genomes, we modelled the selection landscape during the transition from hunting and gathering, to farming and pastoralism across West Eurasia. We identify key selection signals related to metabolism, including that selection at the FADS cluster began earlier than previously reported and that selection near the LCT locus predates the emergence of the lactase persistence allele by thousands of years. We also find strong selection in the HLA region, possibly due to increased exposure to pathogens during the Bronze Age. Using ancient individuals to infer local ancestry tracts in over 400,000 samples from the UK Biobank, we identify widespread differences in the distribution of Mesolithic, Neolithic and Bronze Age ancestries across Eurasia. By calculating ancestry-specific polygenic risk scores, we show that height differences between Northern and Southern Europe are associated with differential Steppe ancestry, rather than selection, and that risk alleles for mood-related phenotypes are enriched for Neolithic farmer ancestry, whereas risk alleles for diabetes and Alzheimer’s disease are enriched for Western hunter-gatherer ancestry. Our results indicate that ancient selection and migration were large contributors to the distribution of phenotypic diversity in present-day Europeans

Genes and environment: novel, functional polymorphism in the human cathepsin L (CTSL1) promoter disrupts a xenobiotic response element (XRE) to alter transcription and blood pressure

Cathepsin L (CTSL1) catalyzes the formation of peptides that influence blood pressure (BP). Naturally occurring genetic variation or targeted ablation of the Ctsl1 locus in mice yield cardiovascular pathology. Here, we searched for genetic variation across the human CTSL1 locus and probed its functional effects, especially in the proximal promoter

Reconsidering Association Testing Methods Using Single-Variant Test Statistics as Alternatives to Pooling Tests for Sequence Data with Rare Variants

Association tests that pool minor alleles into a measure of burden at a locus have been proposed for case-control studies using sequence data containing rare variants. However, such pooling tests are not robust to the inclusion of neutral and protective variants, which can mask the association signal from risk variants. Early studies proposing pooling tests dismissed methods for locus-wide inference using nonnegative single-variant test statistics based on unrealistic comparisons. However, such methods are robust to the inclusion of neutral and protective variants and therefore may be more useful than previously appreciated. In fact, some recently proposed methods derived within different frameworks are equivalent to performing inference on weighted sums of squared single-variant score statistics. In this study, we compared two existing methods for locus-wide inference using nonnegative single-variant test statistics to two widely cited pooling tests under more realistic conditions. We established analytic results for a simple model with one rare risk and one rare neutral variant, which demonstrated that pooling tests were less powerful than even Bonferroni-corrected single-variant tests in most realistic situations. We also performed simulations using variants with realistic minor allele frequency and linkage disequilibrium spectra, disease models with multiple rare risk variants and extensive neutral variation, and varying rates of missing genotypes. In all scenarios considered, existing methods using nonnegative single-variant test statistics had power comparable to or greater than two widely cited pooling tests. Moreover, in disease models with only rare risk variants, an existing method based on the maximum single-variant Cochran-Armitage trend chi-square statistic in the locus had power comparable to or greater than another existing method closely related to some recently proposed methods. We conclude that efficient locus-wide inference using single-variant test statistics should be reconsidered as a useful framework for devising powerful association tests in sequence data with rare variants