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Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci ( P  < 5 × 10 −8 ), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis. A genome-wide association study and Metabochip meta-analysis of body mass index (BMI) detects 97 BMI-associated loci, of which 56 were novel, and many loci have effects on other metabolic phenotypes; pathway analyses implicate the central nervous system in obesity susceptibility and new pathways such as those related to synaptic function, energy metabolism, lipid biology and adipogenesis. Genetic correlates of obesity In the second of two Articles in this issue from the GIANT Consortium, Elizabeth Speliotes and collegues conducted a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), commonly used to define obesity and assess adiposity, to find 97 BMI-associated loci, of which 56 were novel. Many of these loci have significant effects on other metabolic phenotypes. The 97 loci account for about 2.7% of BMI variation, and genome-wide estimates suggest common variation accounts for more than 20% of BMI variation. Pathway analyses implicate the central nervous system in obesity susceptibility including synaptic function, glutamate signaling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

Interindividual differences in drug disposition are important causes for adverse drug reactions and lack of drug response. The majority of phase I and phase II drug-metabolizing enzymes (DMEs) are polymorphic and constitute essential factors for the outcome of drug therapy. Recently, both genome-wide association (GWA) studies with a focus on drug response, as well as more targeted studies of genes encoding DMEs have revealed in-depth information and provided additional information for variation in drug metabolism and drug response, resulting in increased knowledge that aids drug development and clinical practice. In addition, an increasing number of meta-analyses have been published based on several original and often conflicting pharmacogenetic studies. Here, we review data regarding the pharmacogenomics of DMEs, with particular emphasis on novelties. We conclude that recent studies have emphasized the importance of CYP2C19 polymorphism for the effects of clopidogrel, whereas the CYP2C9 polymorphism appears to have a role in anticoagulant treatment, although inferior to VKORC1. Furthermore, the analgesic and side effects of codeine in relation to CYP2D6 polymorphism are supported and the influence of CYP2D6 genotype on breast cancer recurrence during tamoxifen treatment appears relevant as based on three large studies. The influence of CYP2D6 polymorphism on the effect of antidepressants in a clinical setting is yet without any firm evidence, and the relation between CYP2D6 ultrarapid metabolizers and suicide behavior warrants further studies. There is evidence for the influence of CYP3A5 polymorphism on tacrolimus dose, although the influence on response is less studied. Recent large GWA studies support a link between CYP1A2 polymorphism and blood pressure as well as coffee consumption, and between CYP2A6 polymorphism and cigarette consumption, which in turn appears to influence the lung cancer incidence. Regarding phase II enzyme polymorphism, the anticancer treatment with mercaptopurines and irinotecan is still considered important in relation to the polymorphism of TPMT and UGT1A1 , respectively. There is a need for further clarification of the clinical importance and use of all these findings, but the recent research in the field that encompasses larger studies and a whole genome perspective, improves the possibilities be able to make firm and cost-effective recommendations for drug treatment in the future.

ObjectivesMethotrexate has long been used successfully and is preferred worldwide for the treatment of low-risk gestational trophoblastic neoplasia. However, 26.4% of patients develop resistance and require changes to second-line chemotherapy. In the search for personalised treatment approaches, a link has been found between the pharmacogenomics of methotrexate and the response in various diseases. The aim of this study was to explore the effects of ABCB1 and SCLO1B1 gene polymorphisms and the methotrexate treatment response in patients with low-risk gestational trophoblastic neoplasia. Secondary objectives were to investigate the association of single nucleotide polymorphism (SNP) genotypes with toxicity profiles, and to evaluate other factors associated with the response.MethodsRecords of all patients with low-risk gestational trophoblastic neoplasia were reviewed and patients who received methotrexate as a single agent were invited to participate in the study. DNA was extracted from peripheral blood samples from 18 patients and assessed for ABCB1 (3435C>T) and SCLO1B1 (521T>C).ResultsFor the ABCB1 polymorphism, CT was the most common genotype (61.1%), followed by CC (27.8%) and TT (11.1%), indicating that TT had a 1.6-fold higher risk of methotrexate-resistance when compared to the wild-type and heterozygous alleles. The risk of methotrexate-related toxicity was 2.67-fold higher in CT/CC patients who showed a better response to methotrexate. The SCLO1B1 polymorphism was not associated with treatment outcomes.ConclusionsABCB1 polymorphism might be useful as a biomarker for predicting the response to methotrexate in patients with low-risk gestational trophoblastic neoplasia.

BackgroundThe B cell-activating factor (BAFF) promotes the maturation, differentiation, and survival of B lymphocytes, which play an important role in the pathogenesis of systemic lupus erythematosus (SLE). This cytokine has been associated with SLE disease activity, hence TNFSF13B gene, which encodes BAFF, along with its diverse single-nucleotide polymorphisms (SNPs) might also be associated with more severe SLE activity. The aim of this study was to explore the association between TNFSF13B genetic polymorphisms with disease activity, as well as serum soluble BAFF (s-BAFF) levels in SLE patients.MethodsThis cross-sectional study included SLE patients in rheumatology clinic and in-patient wards of Dr. Hasan Sadikin General Hospital, Bandung, between February 2020 -March 2022. One single nucleotide rs9514828 (C>T -871) polymorphism in the 5’ regulatory region of the TNFSF13B gene were identified by PCR-sequencing. Serum BAFF levels were measured by ELISA and disease activity was measured by MEX-SLEDAI score. The active disease was determined by MEX-SLEDAI 2. The statistical analysis was performed using Mann-Whitney, Chi-Square, and Spearman test for the correlation.ResultsThere were 107 SLE patients, all female with median age of 32 years old (interquartile range [IQR], 15–64). The median disease duration was 5 years (IQR 0.5–22), whereas the median s-BAFF levels was 846.9 pg/mL (IQR 185–6979.88). The s-BAFF levels were significantly elevated in active disease patients compared to inactive disease (953.17 pg/ml vs 781.4 pg/mL; p 0.008). There was a weak positive correlation between s-BAFF levels and disease activity (r 0.311; p 0.001). There were no differences in genotype TNFSF13B polymorphisms with the disease activity.ConclusionsAlthough the rs9514828 (C>T -871) of TNFSF13B gene promoter does not seem to be related with SLE activity, s-BAFF levels is, however, correlated with disease activity. Further study to explore other polymorphisms in TNFSF13B gene is of great interest.

Schizophrenia has a heritability of 60–80% 1 , much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4 , and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies. A genome-wide association study including over 76,000 individuals with schizophrenia and over 243,000 control individuals identifies common variant associations at 287 genomic loci, and further fine-mapping analyses highlight the importance of genes involved in synaptic processes.

We studied frequencies of AMPD1 C34T, UCP2 Ala55Val, ACE I/D, BDKRB2 + 9/−9 and NOS3 Glu298Asp variants in a group of triathletes who were participants of Czechman Triathlon Race 2013 in the Czech Republic. Buccal swap samples were taken from 118 competitors but from only 101 of them we gained complete data including the final race time. Our results showed that only frequency AMPD1 CT genotype was significantly overrepresented in a group of athletes who finished the race in 300 min compared to athletes did not (36.1% vs. 12.3%; P = 0.007) while AMPD1 TT genotype was missing in our group of subjects. This test also fails to reject the null hypothesis that the population is in Hardy-Weinberg equilibrium (χ2 = 1,3499; df = 1; p = 0.25). Adenosine monophosphate deaminase (AMPD) is one of the most important regulators of muscle energy metabolism during exercise. AMPD displaces the equilibrium of the myokinase reaction toward ATP production (2 ADP ↔ ATP +AMP) by converting AMP to inosine monophosphate (IMP). An activity of this enzyme, encoded by AMPD1 gene, can be affected by the C34T genetic polymorphism. These results are quite surprising in the light of previously published studies where 34T allele is considered to be relatively unfavourable for sports performance in general. On the other hand, our results are consistent with the recently published study Lifanov et al. (2014) showing higher frequencies of 34T allele in soccer players compared to sedentary controls. Thus 34T allele could potentially be useful for long-term endurance activities.AcknowledgmentThis research has been supported by the project of Ministry of Education Youth and Sport, Czech Republic [PRVOUK n. 38].ReferencesLifanov D, Khadyeva MN, Rahmatullina L, Demenev S V, Ibragimov, RR. Effect of creatine supplementation on physical performance are related to the AMPD1 and PPARG genes polymorphisms in football players. Rossiiskii Fiziologicheskii Zhurnal Imeni I. M. Sechenova, 2014 Jun;100(6):767–776.Sole X, Guino E, Valls J, Iniesta R, Moreno, V. SNPStats: a web tool for the analysis of association studies. Bioinformatics, 2006 Aug;22(15):1928–1929.

Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use 1 . Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels 2 , heart disease remains the leading cause of death worldwide 3 . Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS 4 – 23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns 24 . Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine 25 , we anticipate that increased diversity of participants will lead to more accurate and equitable 26 application of polygenic scores in clinical practice. A genome-wide association meta-analysis study of blood lipid levels in roughly 1.6 million individuals demonstrates the gain of power attained when diverse ancestries are included to improve fine-mapping and polygenic score generation, with gains in locus discovery related to sample size.

Summary Targeted selection and inbreeding have resulted in a lack of genetic diversity in elite hexaploid bread wheat accessions. Reduced diversity can be a limiting factor in the breeding of high yielding varieties and crucially can mean reduced resilience in the face of changing climate and resource pressures. Recent technological advances have enabled the development of molecular markers for use in the assessment and utilization of genetic diversity in hexaploid wheat. Starting with a large collection of 819 571 previously characterized wheat markers, here we describe the identification of 35 143 single nucleotide polymorphism‐based markers, which are highly suited to the genotyping of elite hexaploid wheat accessions. To assess their suitability, the markers have been validated using a commercial high‐density Affymetrix Axiom® genotyping array (the Wheat Breeders’ Array), in a high‐throughput 384 microplate configuration, to characterize a diverse global collection of wheat accessions including landraces and elite lines derived from commercial breeding communities. We demonstrate that the Wheat Breeders’ Array is also suitable for generating high‐density genetic maps of previously uncharacterized populations and for characterizing novel genetic diversity produced by mutagenesis. To facilitate the use of the array by the wheat community, the markers, the associated sequence and the genotype information have been made available through the interactive web site ‘CerealsDB’.

Fast growth is an important and highly desired trait, which affects the profitability of food animal production, with feed costs accounting for the largest proportion of production costs. Traditional phenotype-based selection is typically used to select for growth traits; however, genetic improvement is slow over generations. Single nucleotide polymorphisms (SNPs) explain 90% of the genetic differences between individuals; therefore, they are most suitable for genetic evaluation and strategies that employ molecular genetics for selective breeding. SNPs found within or near a coding sequence are of particular interest because they are more likely to alter the biological function of a protein. We aimed to use SNPs to identify markers and genes associated with genetic variation in growth. RNA-Seq whole-transcriptome analysis of pooled cDNA samples from a population of rainbow trout selected for improved growth versus unselected genetic cohorts (10 fish from 1 full-sib family each) identified SNP markers associated with growth-rate. The allelic imbalances (the ratio between the allele frequencies of the fast growing sample and that of the slow growing sample) were considered at scores >5.0 as an amplification and <0.2 as loss of heterozygosity. A subset of SNPs (n = 54) were validated and evaluated for association with growth traits in 778 individuals of a three-generation parent/offspring panel representing 40 families. Twenty-two SNP markers and one mitochondrial haplotype were significantly associated with growth traits. Polymorphism of 48 of the markers was confirmed in other commercially important aquaculture stocks. Many markers were clustered into genes of metabolic energy production pathways and are suitable candidates for genetic selection. The study demonstrates that RNA-Seq at low sequence coverage of divergent populations is a fast and effective means of identifying SNPs, with allelic imbalances between phenotypes. This technique is suitable for marker development in non-model species lacking complete and well-annotated genome reference sequences.