👤 Domenico A Coviello

Hypertrophic cardiomyopathy (HCM) is mainly associated with myosin, heavy chain 7 (MYH7) and myosin binding protein C, cardiac (MYBPC3) mutations. In order to better explain the clinical and genetic heterogeneity in HCM patients, in this study, we implemented a target-next generation sequencing (NGS) assay. An Ion AmpliSeq™ Custom Panel for the enrichment of 19 genes, of which 9 of these did not encode thick/intermediate and thin myofilament (TTm) proteins and, among them, 3 responsible of HCM phenocopy, was created. Ninety-two DNA samples were analyzed by the Ion Personal Genome Machine: 73 DNA samples (training set), previously genotyped in some of the genes by Sanger sequencing, were used to optimize the NGS strategy, whereas 19 DNA samples (discovery set) allowed the evaluation of NGS performance. In the training set, we identified 72 out of 73 expected mutations and 15 additional mutations: the molecular diagnosis was achieved in one patient with a previously wild-type status and the pre-excitation syndrome was explained in another. In the discovery set, we identified 20 mutations, 5 of which were in genes encoding non-TTm proteins, increasing the diagnostic yield by approximately 20%: a single mutation in genes encoding non-TTm proteins was identified in 2 out of 3 borderline HCM patients, whereas co-occuring mutations in genes encoding TTm and galactosidase alpha (GLA) altered proteins were characterized in a male with HCM and multiorgan dysfunction. Our combined targeted NGS-Sanger sequencing-based strategy allowed the molecular diagnosis of HCM with greater efficiency than using the conventional (Sanger) sequencing alone. Mutant alleles encoding non-TTm proteins may aid in the complete understanding of the genetic and phenotypic heterogeneity of HCM: co-occuring mutations of genes encoding TTm and non-TTm proteins could explain the wide variability of the HCM phenotype, whereas mutations in genes encoding only the non-TTm proteins are identifiable in patients with a milder HCM status. Show less

Sex hormone-binding globulin (SHBG) is a glycoprotein responsible for the transport and biologic availability of sex steroid hormones, primarily testosterone and estradiol. SHBG has been associated with chronic diseases including type 2 diabetes (T2D) and with hormone-sensitive cancers such as breast and prostate cancer. We performed a genome-wide association study (GWAS) meta-analysis of 21,791 individuals from 10 epidemiologic studies and validated these findings in 7,046 individuals in an additional six studies. We identified twelve genomic regions (SNPs) associated with circulating SHBG concentrations. Loci near the identified SNPs included SHBG (rs12150660, 17p13.1, p = 1.8 × 10(-106)), PRMT6 (rs17496332, 1p13.3, p = 1.4 × 10(-11)), GCKR (rs780093, 2p23.3, p = 2.2 × 10(-16)), ZBTB10 (rs440837, 8q21.13, p = 3.4 × 10(-09)), JMJD1C (rs7910927, 10q21.3, p = 6.1 × 10(-35)), SLCO1B1 (rs4149056, 12p12.1, p = 1.9 × 10(-08)), NR2F2 (rs8023580, 15q26.2, p = 8.3 × 10(-12)), ZNF652 (rs2411984, 17q21.32, p = 3.5 × 10(-14)), TDGF3 (rs1573036, Xq22.3, p = 4.1 × 10(-14)), LHCGR (rs10454142, 2p16.3, p = 1.3 × 10(-07)), BAIAP2L1 (rs3779195, 7q21.3, p = 2.7 × 10(-08)), and UGT2B15 (rs293428, 4q13.2, p = 5.5 × 10(-06)). These genes encompass multiple biologic pathways, including hepatic function, lipid metabolism, carbohydrate metabolism and T2D, androgen and estrogen receptor function, epigenetic effects, and the biology of sex steroid hormone-responsive cancers including breast and prostate cancer. We found evidence of sex-differentiated genetic influences on SHBG. In a sex-specific GWAS, the loci 4q13.2-UGT2B15 was significant in men only (men p = 2.5 × 10(-08), women p = 0.66, heterogeneity p = 0.003). Additionally, three loci showed strong sex-differentiated effects: 17p13.1-SHBG and Xq22.3-TDGF3 were stronger in men, whereas 8q21.12-ZBTB10 was stronger in women. Conditional analyses identified additional signals at the SHBG gene that together almost double the proportion of variance explained at the locus. Using an independent study of 1,129 individuals, all SNPs identified in the overall or sex-differentiated or conditional analyses explained ~15.6% and ~8.4% of the genetic variation of SHBG concentrations in men and women, respectively. The evidence for sex-differentiated effects and allelic heterogeneity highlight the importance of considering these features when estimating complex trait variance. 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