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Body composition is often altered in psychiatric disorders. Using genome-wide common genetic variation data, we calculate sex-specific genetic correlations amongst body fat %, fat mass, fat-free mass, physical activity, glycemic traits and 17 psychiatric traits (up to N  = 217,568). Two patterns emerge: (1) anorexia nervosa, schizophrenia, obsessive-compulsive disorder, and education years are negatively genetically correlated with body fat % and fat-free mass, whereas (2) attention-deficit/hyperactivity disorder (ADHD), alcohol dependence, insomnia, and heavy smoking are positively correlated. Anorexia nervosa shows a stronger genetic correlation with body fat % in females, whereas education years is more strongly correlated with fat mass in males. Education years and ADHD show genetic overlap with childhood obesity. Mendelian randomization identifies schizophrenia, anorexia nervosa, and higher education as causal for decreased fat mass, with higher body fat % possibly being a causal risk factor for ADHD and heavy smoking. These results suggest new possibilities for targeted preventive strategies. Psychiatric disorders are often accompanied by alterations in BMI and body composition due to changes in eating behaviour and physical activity. Here, Hübel et al. study the genetic overlap between these traits and find that genetic correlations between psychiatric disorders and body composition are sex-specific and evident only in adulthood.

Background Mapping expression quantitative trait loci (eQTLs) in skeletal muscle tissue in pigs is crucial for understanding the relationship between genetic variation and phenotypic expression of carcass traits in meat animals. Therefore, the primary objective of this study was to evaluate the impact of different sets of single nucleotide polymorphisms (SNP), including scenarios removing SNPs pruned for linkage disequilibrium (LD) and SNPs derived from SNP chip arrays and RNA-seq data from liver, brain, and skeletal muscle tissues, on the identification of eQTLs in the Longissimus lumborum tissue, associated with carcass and body composition traits in Large White pigs. The SNPs identified from muscle mRNA were combined with SNPs identified in the brain and liver tissue transcriptomes, as well as SNPs from the GGP Porcine 50 K SNP chip array. Cis- and trans-eQTLs were identified based on the skeletal muscle gene expression level, followed by functional genomic analyses and statistical associations with carcass and body composition traits in Large White pigs. Results The number of cis- and trans-eQTLs identified across different sets of SNPs (scenarios) ranged from 261 to 2,539 and from 29 to 13,721, respectively. Furthermore, 6,180 genes were modulated by eQTLs in at least one of the scenarios evaluated. The eQTLs identified were not significantly associated with carcass and body composition traits but were significantly enriched for many traits in the “Meat and Carcass” type QTL. The scenarios with the highest number of cis- ( n  = 304) and trans- ( n  = 5,993) modulated genes were the unpruned and LD-pruned SNP set scenarios identified from the muscle transcriptome. These genes include 84 transcription factor coding genes. Conclusions After LD pruning, the set of SNPs identified based on the transcriptome of the skeletal muscle tissue of pigs resulted in the highest number of genes modulated by eQTLs. Most eQTLs are of the trans type and are associated with genes influencing complex traits in pigs, such as transcription factors and enhancers. Furthermore, the incorporation of SNPs from other genomic regions to the set of SNPs identified in the porcine skeletal muscle transcriptome contributed to the identification of eQTLs that had not been identified based on the porcine skeletal muscle transcriptome alone.

Single-nucleotide polymorphisms (SNPs), which are located in the first intron of the FTO gene, are reported to be associated with body weight and the body mass index (BMI). However, their effects on anthropometric measurements in adolescents are poorly understood. This study aimed to investigate the association of three adjacent polymorphisms (rs9930506, rs9930501, & rs9932754) in the FTO gene with anthropometric indices in Iranian adolescent males. The participants comprised a total of 237 adolescent males who were recruited randomly from two high schools in Tehran, Iran. The DNA samples were genotyped for the FTO gene polymorphisms by DNA sequencing. BMI, body fat percentage (BF%), and body muscle percentage (BM%) were determined using a validated bioelectrical impedance analysis scale. The association of the FTO polymorphisms with weight, height, BMI, BF%, and BM% was investigated. A haplotype of rs9930506, rs9930501, and rs9932754 (GGT) in the first intron of the FTO with complete linkage disequilibrium (LD) was found to be significantly associated with higher weight (OR = 1.32), BMI (OR = 5.36) and BF% (OR = 1.46), and lower BM% (OR = 3.59) (all P<0.001). None of the students with GGC genotypes were underweight, while all of the students with AAT genotypes had high muscle mass. A haplotype in the first intron of the FTO gene had a strong association with obesity indices in Iranian adolescent males. The FTO gene polymorphisms might have greater effects on anthropometric indices than what was previously imagined. Moreover, we suggested that the FTO gene exerted their effects on anthropometric measurements through haplotypes (and not single SNPs).

PurposeA common variant of the melatonin receptor 1B (MTNR1B) gene has been related to increased signaling of melatonin, a hormone previously associated with body fatness mainly through effects on energy metabolism. We examined whether the MTNR1B variant affects changes of body fatness and composition in response to a dietary weight loss intervention.MethodsThe MTNR1B rs10830963 variant was genotyped for 722 overweight and obese individuals, who were randomly assigned to one of four diets varying in macronutrient composition. Anthropometric and body composition measurements (DXA scan) were collected at baseline and at 6 and 24 months of follow-up.ResultsStatistically significant interactions were observed between the MTNR1B genotype and low-/high-fat diet on changes in weight, body mass index (BMI), waist circumference (WC) and total body fat (p interaction = 0.01, 0.02, 0.002 and 0.04, respectively), at 6 months of dietary intervention. In the low-fat diet group, increasing number of the sleep disruption-related G allele was significantly associated with a decrease in weight (p = 0.004), BMI (p = 0.005) and WC (p = 0.001). In the high-fat diet group, carrying the G allele was positively associated with changes in body fat (p = 0.03). At 2 years, the associations remained statistically significant for changes in body weight (p = 0.02), BMI (p = 0.02) and WC (p = 0.048) in the low-fat diet group, although the gene–diet interaction became less significant.ConclusionsThe results suggest that carriers of the G allele of the MTNR1B rs10830963 may have a greater improvement in body adiposity and fat distribution when eating a low-fat diet.

Background/objectivesGut microbiome regulates host energy metabolism and adiposity. A recent study identified a genome-wide significant variant in the lactase (LCT) gene that determines gut-microbiome abundance. We investigated whether the LCT variant influenced long-term changes in adiposity among overweight and obese individuals.Subjects/methodsWe included 583 whites with LCT variant rs4988235 (G allele as Bifidobacterium-abundance-increasing allele) who were randomly assigned to one of four weight-loss diets varying in macronutrient contents. Two-year changes in adiposity measures were assessed according to the LCT genotype and weight-loss diets.ResultsWe observed a significant interaction between the LCT genotype and dietary protein intake on changes in whole body total fat mass %, trunk fat %, superficial adipose tissue mass (SAT), visceral adipose tissue mass (VAT), and total adipose tissue mass (TAT) (Pinteraction < 0.05 for all). In response to high-protein diet, carrying the G allele of LCT variant rs4988235 was associated with greater reduction of whole body total fat mass % (β [SE] –0.9 [0.43], P = 0.04), trunk fat % (–1.06 [0.58], P = 0.07), SAT (–0.89 [0.42], P = 0.04), VAT (–0.63 [0.27], P = 0.03), and TAT (–1.69 [0.76], P = 0.03). Conversely, increasing numbers of the G allele tended to be related to less reduction of these outcomes in response to low-protein diet.ConclusionsLong-term improvement of body fat composition and distribution was significantly influenced by the Bifidobacterium-related LCT genotype and dietary protein intake. Overweight and obese individuals with the G allele of LCT variant rs4988235 may benefit improving adiposity by eating a low-calorie, high-protein diet.

Background/Objectives: To investigate associations between Follistatin (FST) gene polymorphisms (SNPs) and baseline musculoskeletal traits, and their interactions with 16-week exercise interventions. Methods: A cohort of 470 untrained Northern Han Chinese adults (208 males, 262 females), sourced from the “Research on Key Technologies for an Exercise and Fitness Expert Guidance System” project, was analyzed. These participants were previously randomly assigned to one of four exercise groups (Hill, Running, Cycling, Combined) or a non-exercising Control group, and completed their respective 16-week protocols. Body composition, bone mineral content (BMC), bone mineral density (BMD), and serum follistatin levels were all assessed pre- and post-intervention. Dual-energy X-ray absorptiometry (DXA) was utilized for the body composition, BMC, and BMD measurements. FST SNPs (rs3797296, rs3797297) were genotyped using matrix assisted laser desorption/ionization time-of-flight mass spectrometer (MALDI-TOF MS) or microarrays. To elucidate the biological mechanisms, we performed in silico functional analyses for rs3797296 and rs3797297. Results: Baseline: In females only, the rs3797297 T allele was associated with higher muscle mass (β = 1.159, 95% confidence interval (CI): 0.202–2.116, P_adj = 0.034) and BMC (β = 0.127, 95% CI: 0.039–0.215, P_adj = 0.009), with the BMC effect significantly mediated by muscle mass. Exercise Response: Interventions improved body composition, particularly in females. Gene-Exercise Interaction: A significant interaction occurred exclusively in women undertaking hill climbing: the rs3797296 G allele was associated with attenuated muscle mass gains (β = −1.126 kg, 95% CI: −1.767 to −0.485, P_adj = 0.034). Baseline follistatin correlated with body composition (stronger in males) and increased post-exercise (primarily in males, Hill/Running groups) but did not mediate SNP effects on exercise adaptation. Functional annotation revealed that rs3797297 is a likely causal variant, acting as a skeletal muscle eQTL for the mitochondrial gene NDUFS4, suggesting a mechanism involving muscle bioenergetics. Conclusions: Findings indicate that FST polymorphisms associate with musculoskeletal traits in Northern Han Chinese. Mechanistic insights from functional annotation reveal potential pathways for these associations, highlighting the potential utility of these genetic markers for optimizing training program design.

The primary purpose of this investigation was to examine the effects of arachidonic acid (ARA) supplementation on functional performance and body composition in trained males. In addition, we performed a secondary study looking at molecular responses of ARA supplementation following an acute exercise bout in rodents. Thirty strength-trained males (age: 20.4 ± 2.1 yrs) were randomly divided into two groups: ARA or placebo (i.e. CTL). Then, both groups underwent an 8-week, 3-day per week, non-periodized training protocol. Quadriceps muscle thickness, whole-body composition scan (DEXA), muscle strength, and power were assessed at baseline and post-test. In the rodent model, male Wistar rats (~250 g, ~8 weeks old) were pre-fed with either ARA or water (CTL) for 8 days and were fed the final dose of ARA prior to being acutely strength trained via electrical stimulation on unilateral plantar flexions. A mixed muscle sample was removed from the exercised and non-exercised leg 3 hours post-exercise. Lean body mass (2.9%, p<0.0005), upper-body strength (8.7%, p<0.0001), and peak power (12.7%, p<0.0001) increased only in the ARA group. For the animal trial, GSK-β (Ser9) phosphorylation (p<0.001) independent of exercise and AMPK phosphorylation after exercise (p-AMPK less in ARA, p = 0.041) were different in ARA-fed versus CTL rats. Our findings suggest that ARA supplementation can positively augment strength-training induced adaptations in resistance-trained males. However, chronic studies at the molecular level are required to further elucidate how ARA combined with strength training affect muscle adaptation.

Aims/hypothesis PPARGC1A and PPARGCB encode transcriptional coactivators that regulate numerous metabolic processes. We tested associations and treatment (i.e. metformin or lifestyle modification) interactions with metabolic traits in the Diabetes Prevention Program, a randomised controlled trial in persons at high risk of type 2 diabetes. Methods We used Tagger software to select 75 PPARGCA1 and 94 PPARGC1B tag single-nucleotide polymorphisms (SNPs) for analysis. These SNPs were tested for associations with relevant cardiometabolic quantitative traits using generalised linear models. Aggregate genetic effects were tested using the sequence kernel association test. Results In aggregate, PPARGC1A variation was strongly associated with baseline triacylglycerol concentrations ( p  = 2.9 × 10 −30 ), BMI ( p  = 2.0 × 10 −5 ) and visceral adiposity ( p  = 1.9 × 10 −4 ), as well as with changes in triacylglycerol concentrations ( p  = 1.7 × 10 −5 ) and BMI ( p  = 9.9 × 10 −5 ) from baseline to 1 year. PPARGC1B variation was only associated with baseline subcutaneous adiposity ( p  = 0.01). In individual SNP analyses, Gly482Ser (rs8192678, PPARGC1A ) was associated with accumulation of subcutaneous adiposity and worsening insulin resistance at 1 year (both p  < 0.05), while rs2970852 ( PPARGC1A ) modified the effects of metformin on triacylglycerol levels ( p interaction  = 0.04). Conclusions/interpretation These findings provide several novel and other confirmatory insights into the role of PPARGC1A variation with respect to diabetes-related metabolic traits. Trial registration ClinicalTrials.gov NCT00004992

Aims/hypothesis Peroxisome proliferator-activated receptor γ (PPARγ), encoded by the PPARG gene, regulates insulin sensitivity and adipogenesis, and may bind polyunsaturated fatty acids (PUFA) and thiazolidinediones in a ligand-dependent manner. The PPARG proline for alanine substitution at position 12 (Pro12Ala polymorphism) has been related with obesity directly and via interaction with PUFA. Methods We tested the effect-modifying role of Pro12Ala on the 1 year change in obesity-related traits in a randomised clinical trial of treatment with metformin (n = 989), troglitazone (n = 363) or lifestyle modification (n = 1,004) vs placebo (n = 1,000) for diabetes prevention in high-risk individuals. Results At baseline, Ala12 carriers had larger waists (p < 0.001) and, in a subset, more subcutaneous adipose tissue (SAT; lumbar 2/3; p = 0.04) than Pro12 homozygotes. There was a genotype-by-intervention interaction on 1-year weight change (p = 0.01); in the placebo arm, Pro12 homozygotes gained weight and Ala12 carriers lost weight (p = 0.001). In the metformin and lifestyle arms, weight loss occurred across genotypes, but was greatest in Ala12 carriers (p < 0.05). Troglitazone treatment induced weight gain, which tended to be greater in Ala12 carriers (p = 0.08). In the placebo group, SAT (lumbar 2/3, lumbar 4/5) decreased in Ala12 allele carriers, but was unchanged in Pro12 homozygotes (p <= 0.005). With metformin treatment, SAT decreased independently of genotype. In the lifestyle arm, SAT (lumbar 2/3) reductions occurred across genotypes, but were greater in Ala12 carriers (p = 0.03). A genotype-by-PUFA intake interaction on reduction in visceral fat (lumbar 4/5; p = 0.04) was also observed, which was most evident with metformin treatment (p < 0.001). Conclusions/interpretation Within the Diabetes Prevention Program, the Ala12 allele influences central obesity, an effect which may differ by treatment group and dietary PUFA intake (ClinicalTrials.gov ID no: NCT00004992).

Accurate prediction of an individual’s phenotype from their DNA sequence is one of the great promises of genomics and precision medicine. We extend a powerful individual-level data Bayesian multiple regression model (BayesR) to one that utilises summary statistics from genome-wide association studies (GWAS), SBayesR. In simulation and cross-validation using 12 real traits and 1.1 million variants on 350,000 individuals from the UK Biobank, SBayesR improves prediction accuracy relative to commonly used state-of-the-art summary statistics methods at a fraction of the computational resources. Furthermore, using summary statistics for variants from the largest GWAS meta-analysis ( n ≈ 700, 000) on height and BMI, we show that on average across traits and two independent data sets that SBayesR improves prediction R 2 by 5.2% relative to LDpred and by 26.5% relative to clumping and p  value thresholding. Various approaches are being used for polygenic prediction including Bayesian multiple regression methods that require access to individual-level genotype data. Here, the authors extend BayesR to utilise GWAS summary statistics (SBayesR) and show that it outperforms other summary statistic-based methods.