👤 Serena Sanna

Genetic susceptibility to metabolic associated fatty liver disease (MAFLD) is complex and poorly characterized. Accurate characterization of the genetic background of hepatic fat content would provide insights into disease etiology and causality of risk factors. We performed genome-wide association study (GWAS) on two noninvasive definitions of hepatic fat content: magnetic resonance imaging proton density fat fraction (MRI-PDFF) in 16,050 participants and fatty liver index (FLI) in 388,701 participants from the United Kingdom (UK) Biobank (UKBB). Heritability, genetic overlap, and similarity between hepatic fat content phenotypes were analyzed, and replicated in 10,398 participants from the University Medical Center Groningen (UMCG) Genetics Lifelines Initiative (UGLI). Meta-analysis of GWASs of MRI-PDFF in UKBB revealed five statistically significant loci, including two novel genomic loci harboring CREB3L1 (rs72910057-T, P = 5.40E-09) and GCM1 (rs1491489378-T, P = 3.16E-09), respectively, as well as three previously reported loci: PNPLA3, TM6SF2, and APOE. GWAS of FLI in UKBB identified 196 genome-wide significant loci, of which 49 were replicated in UGLI, with top signals in ZPR1 (P = 3.35E-13) and FTO (P = 2.11E-09). Statistically significant genetic correlation (rg) between MRI-PDFF (UKBB) and FLI (UGLI) GWAS results was found (rg = 0.5276, P = 1.45E-03). Novel MRI-PDFF genetic signals (CREB3L1 and GCM1) were replicated in the FLI GWAS. We identified two novel genes for MRI-PDFF and 49 replicable loci for FLI. Despite a difference in hepatic fat content assessment between MRI-PDFF and FLI, a substantial similar genetic architecture was found. FLI is identified as an easy and reliable approach to study hepatic fat content at the population level. Show less

Non-alcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease in both adults and children. Along with obesity and metabolic syndrome, genetic predisposition influences the progression of NAFLD. Here, we investigated the effect of lifespan/healthspan-related single nucleotide polymorphisms (SNPs) on metabolically associated fatty liver disease in children. We evaluated the impact of 10 SNPs involved in both human liver/metabolic diseases and healthspan (interleukin-6 [IL-6] rs1800795, antisense non coding RNA in the INK4 locus (ANRIL) rs1556516, SH2B3/ATXN2 rs7137828, FURIN rs17514846, TP53 rs1042522, APOC3 rs2542052, KL rs9536314, KL rs9527025, SIRT6 rs107251, FOXO3 rs2802292) on NAFLD-related metabolic and liver features in 177 pediatric patients with biopsy-proven NAFLD, by comparing them to 146 healthy controls. We then applied a multidimensional reduction (MDR) case-control analysis of SNP-SNP interactions, to identify the joint effect of analyzed SNPs in predicting NAFLD and associated features. Discrete SNPs were significantly associated with individual metabolic NAFLD features, but none of them significantly associated with NAFLD diagnosis. By testing potential synergies using the MDR approach, the best combination to diagnose NAFLD (P = 0.0011) resulted in the one encompassing IL-6 rs1800795 and ANRIL rs1556516. Consistently, the risk combinations suggested by SNP-SNP analysis strongly associated with a higher level of fasting plasma blood glucose level (P = 0.024). In conclusion, here we demonstrated a synergic interaction between IL-6 rs1800795 and ANRIL rs1556516 in the diagnosis of NAFLD, and NAFLD-associated hyperglycemia in children. Larger studies are required to confirm our findings and to elucidate mechanisms by which the genetic interaction between these two genes influences healthspan in pediatric NAFLD. Show less

This study is primarily aimed at assessing serum changes on a large panel of proteins in patients with chronic back pain following spa therapy, as well as evaluating different spa therapy regimens as a preliminary exploratory clinical study. Sixty-six patients with chronic back pain secondary to osteoarthritis were randomly enrolled and treated with daily mud packs and bicarbonate-alkaline mineral water baths, or a thermal hydrotherapy rehabilitation scheme, the combination of the two regimens or usual medication only (control group), for two weeks. Clinical variables were evaluated at baseline, after 2 and 12 weeks. One thousand serum proteins were tested before and after a two-week mud bath therapy. All spa treatment groups showed clinical benefit as determined by improvements in VAS pain, Roland Morris disability questionnaire and neck disability index at both time points. The following serum proteins were found greatly increased (≥2.5 fold) after spa treatment: inhibin beta A subunit (INHBA), activin A receptor type 2B (ACVR2B), angiopoietin-1 (ANGPT1), beta-2-microglobulin (B2M), growth differentiation factor 10 (GDF10), C-X-C motif chemokine ligand 5 (CXCL5), fibroblast growth factor 2 (FGF2), fibroblast growth factor 12 (FGF12), oxidized low density lipoprotein receptor 1 (OLR1), matrix metallopeptidase 13 (MMP13). Three proteins were found greatly decreased (≤0.65 fold): apolipoprotein C-III (Apoc3), interleukin 23 alpha subunit p19 (IL23A) and syndecan-1 (SDC1). Spa therapy was confirmed as beneficial for chronic back pain and proved to induce changes in proteins involved in functions such as gene expression modulation, differentiation, angiogenesis, tissue repair, acute and chronic inflammatory response. Show less

We screened variants on an exome-focused genotyping array in >300,000 participants (replication in >280,000 participants) and identified 444 independent variants in 250 loci significantly associated with total cholesterol (TC), high-density-lipoprotein cholesterol (HDL-C), low-density-lipoprotein cholesterol (LDL-C), and/or triglycerides (TG). At two loci (JAK2 and A1CF), experimental analysis in mice showed lipid changes consistent with the human data. We also found that: (i) beta-thalassemia trait carriers displayed lower TC and were protected from coronary artery disease (CAD); (ii) excluding the CETP locus, there was not a predictable relationship between plasma HDL-C and risk for age-related macular degeneration; (iii) only some mechanisms of lowering LDL-C appeared to increase risk for type 2 diabetes (T2D); and (iv) TG-lowering alleles involved in hepatic production of TG-rich lipoproteins (TM6SF2 and PNPLA3) tracked with higher liver fat, higher risk for T2D, and lower risk for CAD, whereas TG-lowering alleles involved in peripheral lipolysis (LPL and ANGPTL4) had no effect on liver fat but decreased risks for both T2D and CAD. Show less

Advances in exome sequencing and the development of exome genotyping arrays are enabling explorations of association between rare coding variants and complex traits. To ensure power for these rare variant analyses, a variety of association tests that group variants by gene or functional unit have been proposed. Here, we extend these tests to family-based studies. We develop family-based burden tests, variable frequency threshold tests and sequence kernel association tests. Through simulations, we compare the performance of different tests. We describe situations where family-based studies provide greater power than studies of unrelated individuals to detect rare variants associated with moderate to large changes in trait values. Broadly speaking, we find that when sample sizes are limited and only a modest fraction of all trait-associated variants can be identified, family samples are more powerful. Finally, we illustrate our approach by analyzing the relationship between coding variants and levels of high-density lipoprotein (HDL) cholesterol in 11,556 individuals from the HUNT and SardiNIA studies, demonstrating association for coding variants in the APOC3, CETP, LIPC, LIPG, and LPL genes and illustrating the value of family samples, meta-analysis, and gene-level tests. Our methods are implemented in freely available C++ code. Show less

Genetic loci for body mass index (BMI) in adolescence and young adulthood, a period of high risk for weight gain, are understudied, yet may yield important insight into the etiology of obesity and early intervention. To identify novel genetic loci and examine the influence of known loci on BMI during this critical time period in late adolescence and early adulthood, we performed a two-stage meta-analysis using 14 genome-wide association studies in populations of European ancestry with data on BMI between ages 16 and 25 in up to 29 880 individuals. We identified seven independent loci (P < 5.0 × 10⁻⁸) near FTO (P = 3.72 × 10⁻²³), TMEM18 (P = 3.24 × 10⁻¹⁷), MC4R (P = 4.41 × 10⁻¹⁷), TNNI3K (P = 4.32 × 10⁻¹¹), SEC16B (P = 6.24 × 10⁻⁹), GNPDA2 (P = 1.11 × 10⁻⁸) and POMC (P = 4.94 × 10⁻⁸) as well as a potential secondary signal at the POMC locus (rs2118404, P = 2.4 × 10⁻⁵ after conditioning on the established single-nucleotide polymorphism at this locus) in adolescents and young adults. To evaluate the impact of the established genetic loci on BMI at these young ages, we examined differences between the effect sizes of 32 published BMI loci in European adult populations (aged 18-90) and those observed in our adolescent and young adult meta-analysis. Four loci (near PRKD1, TNNI3K, SEC16B and CADM2) had larger effects and one locus (near SH2B1) had a smaller effect on BMI during adolescence and young adulthood compared with older adults (P < 0.05). These results suggest that genetic loci for BMI can vary in their effects across the life course, underlying the importance of evaluating BMI at different ages. Show less

Concentrations of liver enzymes in plasma are widely used as indicators of liver disease. We carried out a genome-wide association study in 61,089 individuals, identifying 42 loci associated with concentrations of liver enzymes in plasma, of which 32 are new associations (P = 10(-8) to P = 10(-190)). We used functional genomic approaches including metabonomic profiling and gene expression analyses to identify probable candidate genes at these regions. We identified 69 candidate genes, including genes involved in biliary transport (ATP8B1 and ABCB11), glucose, carbohydrate and lipid metabolism (FADS1, FADS2, GCKR, JMJD1C, HNF1A, MLXIPL, PNPLA3, PPP1R3B, SLC2A2 and TRIB1), glycoprotein biosynthesis and cell surface glycobiology (ABO, ASGR1, FUT2, GPLD1 and ST3GAL4), inflammation and immunity (CD276, CDH6, GCKR, HNF1A, HPR, ITGA1, RORA and STAT4) and glutathione metabolism (GSTT1, GSTT2 and GGT), as well as several genes of uncertain or unknown function (including ABHD12, EFHD1, EFNA1, EPHA2, MICAL3 and ZNF827). Our results provide new insight into genetic mechanisms and pathways influencing markers of liver function. Show less

Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ∼ 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10⁻⁸), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation. Show less

Genetic studies might provide new insights into the biological mechanisms underlying lipid metabolism and risk of CAD. We therefore conducted a genome-wide association study to identify novel genetic determinants of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides. We combined genome-wide association data from 8 studies, comprising up to 17 723 participants with information on circulating lipid concentrations. We did independent replication studies in up to 37 774 participants from 8 populations and also in a population of Indian Asian descent. We also assessed the association between single-nucleotide polymorphisms (SNPs) at lipid loci and risk of CAD in up to 9 633 cases and 38 684 controls. We identified 4 novel genetic loci that showed reproducible associations with lipids (probability values, 1.6×10(-8) to 3.1×10(-10)). These include a potentially functional SNP in the SLC39A8 gene for HDL-C, an SNP near the MYLIP/GMPR and PPP1R3B genes for LDL-C, and at the AFF1 gene for triglycerides. SNPs showing strong statistical association with 1 or more lipid traits at the CELSR2, APOB, APOE-C1-C4-C2 cluster, LPL, ZNF259-APOA5-A4-C3-A1 cluster and TRIB1 loci were also associated with CAD risk (probability values, 1.1×10(-3) to 1.2×10(-9)). We have identified 4 novel loci associated with circulating lipids. We also show that in addition to those that are largely associated with LDL-C, genetic loci mainly associated with circulating triglycerides and HDL-C are also associated with risk of CAD. These findings potentially provide new insights into the biological mechanisms underlying lipid metabolism and CAD risk. Show less

Higher resting heart rate is associated with increased cardiovascular disease and mortality risk. Though heritable factors play a substantial role in population variation, little is known about specific genetic determinants. This knowledge can impact clinical care by identifying novel factors that influence pathologic heart rate states, modulate heart rate through cardiac structure and function or by improving our understanding of the physiology of heart rate regulation. To identify common genetic variants associated with heart rate, we performed a meta-analysis of 15 genome-wide association studies (GWAS), including 38,991 subjects of European ancestry, estimating the association between age-, sex- and body mass-adjusted RR interval (inverse heart rate) and approximately 2.5 million markers. Results with P < 5 × 10(-8) were considered genome-wide significant. We constructed regression models with multiple markers to assess whether results at less stringent thresholds were likely to be truly associated with RR interval. We identified six novel associations with resting heart rate at six loci: 6q22 near GJA1; 14q12 near MYH7; 12p12 near SOX5, c12orf67, BCAT1, LRMP and CASC1; 6q22 near SLC35F1, PLN and c6orf204; 7q22 near SLC12A9 and UfSp1; and 11q12 near FADS1. Associations at 6q22 400 kb away from GJA1, at 14q12 MYH6 and at 1q32 near CD34 identified in previously published GWAS were confirmed. In aggregate, these variants explain approximately 0.7% of RR interval variance. A multivariant regression model including 20 variants with P < 10(-5) increased the explained variance to 1.6%, suggesting that some loci falling short of genome-wide significance are likely truly associated. Future research is warranted to elucidate underlying mechanisms that may impact clinical care. Show less

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes. Show less

To identify loci for age at menarche, we performed a meta-analysis of 32 genome-wide association studies in 87,802 women of European descent, with replication in up to 14,731 women. In addition to the known loci at LIN28B (P = 5.4 × 10⁻⁶⁰) and 9q31.2 (P = 2.2 × 10⁻³³), we identified 30 new menarche loci (all P < 5 × 10⁻⁸) and found suggestive evidence for a further 10 loci (P < 1.9 × 10⁻⁶). The new loci included four previously associated with body mass index (in or near FTO, SEC16B, TRA2B and TMEM18), three in or near other genes implicated in energy homeostasis (BSX, CRTC1 and MCHR2) and three in or near genes implicated in hormonal regulation (INHBA, PCSK2 and RXRG). Ingenuity and gene-set enrichment pathway analyses identified coenzyme A and fatty acid biosynthesis as biological processes related to menarche timing. Show less

Blood low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol and triglyceride levels are risk factors for cardiovascular disease. To dissect the polygenic basis of these traits, we conducted genome-wide association screens in 19,840 individuals and replication in up to 20,623 individuals. We identified 30 distinct loci associated with lipoprotein concentrations (each with P < 5 x 10(-8)), including 11 loci that reached genome-wide significance for the first time. The 11 newly defined loci include common variants associated with LDL cholesterol near ABCG8, MAFB, HNF1A and TIMD4; with HDL cholesterol near ANGPTL4, FADS1-FADS2-FADS3, HNF4A, LCAT, PLTP and TTC39B; and with triglycerides near AMAC1L2, FADS1-FADS2-FADS3 and PLTP. The proportion of individuals exceeding clinical cut points for high LDL cholesterol, low HDL cholesterol and high triglycerides varied according to an allelic dosage score (P < 10(-15) for each trend). These results suggest that the cumulative effect of multiple common variants contributes to polygenic dyslipidemia. Show less

To identify genetic variants influencing plasma lipid concentrations, we first used genotype imputation and meta-analysis to combine three genome-wide scans totaling 8,816 individuals and comprising 6,068 individuals specific to our study (1,874 individuals from the FUSION study of type 2 diabetes and 4,184 individuals from the SardiNIA study of aging-associated variables) and 2,758 individuals from the Diabetes Genetics Initiative, reported in a companion study in this issue. We subsequently examined promising signals in 11,569 additional individuals. Overall, we identify strongly associated variants in eleven loci previously implicated in lipid metabolism (ABCA1, the APOA5-APOA4-APOC3-APOA1 and APOE-APOC clusters, APOB, CETP, GCKR, LDLR, LPL, LIPC, LIPG and PCSK9) and also in several newly identified loci (near MVK-MMAB and GALNT2, with variants primarily associated with high-density lipoprotein (HDL) cholesterol; near SORT1, with variants primarily associated with low-density lipoprotein (LDL) cholesterol; near TRIB1, MLXIPL and ANGPTL3, with variants primarily associated with triglycerides; and a locus encompassing several genes near NCAN, with variants strongly associated with both triglycerides and LDL cholesterol). Notably, the 11 independent variants associated with increased LDL cholesterol concentrations in our study also showed increased frequency in a sample of coronary artery disease cases versus controls. Show less