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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.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures ( P  < 5 × 10 −8 ). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms. Genome-wide association meta-analyses of waist-to-hip ratio adjusted for body mass index in more than 224,000 individuals identify 49 loci, 33 of which are new and many showing significant sexual dimorphism with a stronger effect in women; pathway analyses implicate adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution. Cardiometabolic traits linked to body fat distribution In the first of a pair of Articles in this issue from the GIANT Consortium, genome-wide association meta-analyses of waist and hip circumference-related traits in more than 200,000 individuals have been used to identify 49 loci — 33 of them new — associated with waist-to-hip ratio adjusted for body mass index and an additional 19 loci associated with related waist and hip circumference measures. A subset of these loci shows significant sexual dimorphism, with many showing a stronger effect in women. Analyses implicate adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms and offer potential targets for interventions in the risks associated with abdominal fat accumulation.

CYP3A, a key member of the cytochrome P450 (CYP450) superfamily, is integral to drug metabolism, processing a substantial portion of medications. Their role in drug metabolism is particularly prominent, as CYP3A4 and CYP3A5 metabolize approximately 30–50% of known drugs. The genetic polymorphism of CYP3A4/5 is significant inter-individual variability in enzymatic activity, which can result in different pharmacokinetic profiles in response to the same drug among individuals. These polymorphisms can lead to either increased drug toxicity or reduced therapeutic effects, requiring dosage adjustments based on genetic profiles. Consequently, the study of the enzymatic activity of CYP3A4/5 gene variants is of great importance for the formulation of personalized treatment regimens. This article first reviews the role of CYP3A4/5 in drug metabolism in the human body, including inhibitors and inducers of CYP3A4/5 and drug-drug interactions. In terms of genetic polymorphism, it discusses the detection methods, enzymatic kinetic characteristics, and clinical guidelines for CYP3A5. Finally, the article summarizes the importance of CYP3A4/5 in clinical applications, including personalized therapy, management of drug-drug interactions, and adjustment of drug doses. This review contributes to the understanding of the functions and genetic characteristics of CYP3A4/5, allowing for more effective clinical outcomes through optimized drug therapy.

Nearly 100 genes and functional polymorphisms underlying natural variation in plant development and physiology have been identified. In crop plants, these include genes involved in domestication traits, such as those related to plant architecture, fruit and seed structure and morphology, as well as yield and quality traits improved by subsequent crop breeding. In wild plants, comparable traits have been dissected mainly in Arabidopsis thaliana. In this review, we discuss the major contributions of the analysis of natural variation to our understanding of plant development and physiology, focusing in particular on the timing of germination and flowering, plant growth and morphology, primary metabolism, and mineral accumulation. Overall, functional polymorphisms appear in all types of genes and gene regions, and they may have multiple mutational causes. However, understanding this diversity in relation to adaptation and environmental variation is a challenge for which tools are now available.

The genus Rhododendron, known for large impressive flowers is widely distributed throughout the world. Rhododendrons have limited genetic information, despite of comprising high species diversity, morphological overlap and weak genetic barrier. In present study, expressed sequence tag (EST) data from Rhododendron catawbiense  Michx (Subgenus Hymenanthes, Section Ponticum) and Rhododendron mucronatum var. ripense (Makino) E.H. Wilson (Subgenus Tsutsusi, Section Tsutsusi) were utilized for mining and identification of the SSRs for genetic diversity analysis of R. arboreum Smith (Subgenus Tsutsusi, Section Tsutsusi). A total of 249 SSRs were developed from 1767 contigs. Di-nucleotide was found to be most abundant repeat followed by tri- and tetra-nucleotide repeats. The motif AG/CT was most common di-nucleotide motif (31.73%), whereas, AAC/GTT (8.43%), ACG/CGT (8.03%), AAG/CTT (7.23%) and AGG/CCT (6.43%) were most abundant tri-nucleotide repeat motif. Among these SSRs, 168 sequences were only fit into the criteria to design flanking primer pairs. A total of 30 randomly selected primer pairs were utilized for validation and genetic diversity study in 36 genotypes of R. arboreum collected from western Himalayan region. In aggregate, 26 SSR markers (86.66%) produced good and repeatable amplifications. Expected heterozygosity ( H E ) ranged from 0.322 to 0.841 and observed heterozygosity ( H O ) ranged from 0.327 to 1.000 and PIC value ranged from 0.008 to 0.786. These primers were able to distinguish the geographic differences of occurrence based on cluster analysis. These developed EST-SSRs can be useful in future population genetics analysis and micro-evolutionary studies in Rhododendron species.

The relationship between selenium and metabolic syndrome (MetS) has been discussed controversially, and limited studies have examined the associations of single nucleotide polymorphisms in selenoproteins genes with MetS. Hence, to examine the associations of plasma selenium concentrations and selenoprotein P rs7579 polymorphism with MetS, a case-control study of 1279 MetS cases and 1279 sex- and age- (±2 years) matched controls was conducted based on the baseline data of the Tongji-Ezhou Cohort study. Plasma selenium concentrations were measured by inductively coupled plasma mass spectrometry. MetS was defined using the definition of the Joint Interim Statement, adjusted for the Chinese population. In addition, the rs7579 polymorphism was genotyped by the Agena MassARRAY System. Plasma selenium concentrations in the MetS group were higher than in the control group (93.88 μg/L (83.17-107.41) vs. 92.66 μg/L (82.36-103.53), P<0.05). Compared with quartile 4 (≥103.53 μg/L), the multivariate-adjusted odds ratios (ORs) and 95% confidence intervals (CIs) associated with MetS were 0.79 (0.59-1.06) for quartile 1 (<82.36 μg/L), 0.75 (0.56-1.01) for quartile 2 (82.37-92.66 μg/L), and 0.61 (0.45-0.83) for quartile 3 (92.67-103.52 μg/L). The cubic spline analyses revealed a U-shaped association between plasma selenium and MetS, with the lowest risk at around 93.69 μg/L. Moreover, in cubic spline analyses, plasma selenium showed U-shaped associations with central obesity and high blood pressure, positive associations with hypertriglyceridemia and hyperglycemia, and a negative association with low high-density lipoprotein cholesterol. Additionally, both the GA and GA+AA genotype carriers were associated with increased ORs of MetS comparing with the GG genotype carriers. Our findings suggested a U-shaped association between plasma selenium and MetS and diverse associations between plasma selenium and components of MetS. Furthermore, our study found that the A allele of rs7579 was associated with higher odds of MetS. Further studies are needed to confirm our findings and elucidate the underlying mechanisms.

We use a genome-wide association of 1 million parental lifespans of genotyped subjects and data on mortality risk factors to validate previously unreplicated findings near CDKN2B-AS1, ATXN2/BRAP, FURIN/FES, ZW10, PSORS1C3, and 13q21.31, and identify and replicate novel findings near ABO, ZC3HC1, and IGF2R. We also validate previous findings near 5q33.3/EBF1 and FOXO3, whilst finding contradictory evidence at other loci. Gene set and cell-specific analyses show that expression in foetal brain cells and adult dorsolateral prefrontal cortex is enriched for lifespan variation, as are gene pathways involving lipid proteins and homeostasis, vesicle-mediated transport, and synaptic function. Individual genetic variants that increase dementia, cardiovascular disease, and lung cancer – but not other cancers – explain the most variance. Resulting polygenic scores show a mean lifespan difference of around five years of life across the deciles. Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter ). Ageing happens to us all, and as the cabaret singer Maurice Chevalier pointed out, \"old age is not that bad when you consider the alternative\". Yet, the growing ageing population of most developed countries presents challenges to healthcare systems and government finances. For many older people, long periods of ill health are part of the end of life, and so a better understanding of ageing could offer the opportunity to prolong healthy living into old age. Ageing is complex and takes a long time to study – a lifetime in fact. This makes it difficult to discern its causes, among the countless possibilities based on an individual’s genes, behaviour or environment. While thousands of regions in an individual’s genetic makeup are known to influence their risk of different diseases, those that affect how long they will live have proved harder to disentangle. Timmers et al. sought to pinpoint such regions, and then use this information to predict, based on their DNA, whether someone had a better or worse chance of living longer than average. The DNA of over 500,000 people was read to reveal the specific ‘genetic fingerprints’ of each participant. Then, after asking each of the participants how long both of their parents had lived, Timmers et al. pinpointed 12 DNA regions that affect lifespan. Five of these regions were new and had not been linked to lifespan before. Across the twelve as a whole several were known to be involved in Alzheimer’s disease, smoking-related cancer or heart disease. Looking at the entire genome, Timmers et al. could then predict a lifespan score for each individual, and when they sorted participants into ten groups based on these scores they found that top group lived five years longer than the bottom, on average. Many factors beside genetics influence how long a person will live and our lifespan cannot be read from our DNA alone. Nevertheless, Timmers et al. had hoped to narrow down their search and discover specific genes that directly influence how quickly people age, beyond diseases. If such genes exist, their effects were too small to be detected in this study. The next step will be to expand the study to include more participants, which will hopefully pinpoint further genomic regions and help disentangle the biology of ageing and disease.

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.

The 6 main milk proteins in cattle are encoded by highly polymorphic genes characterized by several nonsynonymous and synonymous mutations, with up to 47 protein variants identified. Such an extensive variation was used for linkage analysis with the description of the casein cluster more than 30 yr ago and has been applied to animal breeding for several years. Casein haplotype effects on productive traits have been investigated considering information on the whole casein complex. Moreover, mutations within the noncoding sequences have been shown to affect the specific protein expression and, as a consequence, milk composition and cheesemaking. Milk protein variants are also a useful tool for breed characterization, diversity, and phylogenetic studies. In addition, they are involved in various aspects of human nutrition. First, the occurrence of alleles associated with a reduced content of different caseins might be exploited for the production of milk with particular nutritional qualities; that is, hypoallergenic milk. On the other hand, the frequency of these alleles can be decreased by selection of sires using simple DNA tests, thereby increasing the casein content in milk used for cheesemaking. Furthermore, the biological activity of peptides released from milk protein digestion can be affected by amino acid exchanges or deletions resulting from gene mutations. Finally, the gene-culture coevolution between cattle milk protein genes and human lactase genes, which has been recently highlighted, is impressive proof of the nonrandom occurrence of milk protein genetic variation over the centuries.

HMG Co-A reductase inhibitors are ubiquitous in our community yet their potential role in age-related macular degeneration (AMD) remains to be determined. To evaluate the effect of simvastatin on AMD progression and the effect modification by polymorphism in apolipoprotein E (ApoE) and complement factor H (CFH) genes. A proof of concept double-masked randomized controlled study. 114 participants aged 53 to 91 years, with either bilateral intermediate AMD or unilateral non-advanced AMD (with advanced AMD in fellow eye), BCVA ≥ 20/60 in at least one eye, and a normal lipid profile. Simvastatin 40 mg/day or placebo, allocated 1:1. Progression of AMD either to advanced AMD or in severity of non-advanced AMD. Results. The cumulative AMD progression rates were 70% in the placebo and 54% in the simvastatin group. Intent to treat multivariable logistic regression analysis, adjusted for age, sex, smoking and baseline AMD severity, showed a significant 2-fold decrease in the risk of progression in the simvastatin group: OR 0.43 (0.18-0.99), p = 0.047. Post-hoc analysis stratified by baseline AMD severity showed no benefit from treatment in those who had advanced AMD in the fellow eye before enrolment: OR 0.97 (0.27-3.52), p = 0.96, after adjusting for age, sex and smoking. However, there was a significant reduction in the risk of progression in the bilateral intermediate AMD group compared to placebo [adjusted OR 0.23 (0.07-0.75), p = 0.015]. The most prominent effect was observed amongst those who had the CC (Y402H) at risk genotype of the CFH gene [OR 0.08 (0.02-0.45), p = 0.004]. No evidence of harm from simvastatin intervention was detected. Simvastatin may slow progression of non-advanced AMD, especially for those with the at risk CFH genotype CC (Y402H). Further exploration of the potential use of statins for AMD, with emphasis on genetic subgroups, is warranted. Australian New Zealand Clinical Trial Registry (ANZCTR) ACTRN1260500032065.