Genome-wide association identifies nine common variants associated with fasting proinsulin levels and provides new insights into the pathophysiology of type 2 diabetes.

OBJECTIVE: Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology. RESEARCH DESIGN AND METHODS: We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates. RESULTS: Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10(-8)). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10(-4)), improved β-cell function (P = 1.1 × 10(-5)), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10(-6)). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets. CONCLUSIONS: We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis

The genetic architecture of type 2 diabetes

The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of heritability. To test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole genome sequencing in 2,657 Europeans with and without diabetes, and exome sequencing in a total of 12,940 subjects from five ancestral groups. To increase statistical power, we expanded sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support a major role for lower-frequency variants in predisposition to type 2 diabetes

Rare and low-frequency coding variants alter human adult height

Height is a highly heritable, classic polygenic trait with ~700 common associated variants identified so far through genome - wide association studies . Here , we report 83 height - associated coding variants with lower minor allele frequenc ies ( range of 0.1 - 4.8% ) and effects of up to 2 16 cm /allele ( e.g. in IHH , STC2 , AR and CRISPLD2 ) , >10 times the average effect of common variants . In functional follow - up studies, rare height - increasing alleles of STC2 (+1 - 2 cm/allele) compromise d proteolytic inhibition of PAPP - A and increased cleavage of IGFBP - 4 in vitro , resulting in higher bioavailability of insulin - like growth factors . The se 83 height - associated variants overlap genes mutated in monogenic growth disorders and highlight new biological candidates ( e.g. ADAMTS3, IL11RA, NOX4 ) and pathways ( e.g . proteoglycan/ glycosaminoglycan synthesis ) involved in growth . Our results demonstrate that sufficiently large sample sizes can uncover rare and low - frequency variants of moderate to large effect associated with polygenic human phenotypes , and that these variants implicate relevant genes and pathways

New genetic loci link adipose and insulin biology to body fat distribution.

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

Selective quantification of the neurotoxin BMAA by use of hydrophilic-interaction liquid chromatography\u2013differential mobility spectrometry\u2013tandem mass spectrometry (HILIC\u2013DMS\u2013MS\u2013MS)

The neurotoxin \u3b2-N-methylamino-l-alanine (BMAA) has been reported in cyanobacteria and shellfish, raising concerns about widespread human exposure. However, inconsistent results for BMAA analysis have led to controversy. Liquid chromatography\u2013tandem mass spectrometry (LC\u2013MS\u2013MS) is the most appropriate method for analysis of BMAA, but the risk of interference from isomers, other sample components, and the electrospray background is still present. We have investigated differential mobility spectrometry (DMS) as an ion filter to improve selectivity in the hydrophilic interaction liquid chromatographic (HILIC)\u2013MS\u2013MS determination of BMAA. We obtained standards for two BMAA isomers not previously analyzed by HILIC\u2013MS, \u3b2-amino-N-methylalanine and 3,4-diaminobutanoic acid, and the typically used 2,4-diaminobutanoic acid and N-(2-aminoethyl)glycine. DMS separation of BMAA from these isomers was achieved and optimized conditions were used to develop a sensitive and highly selective multidimensional HILIC\u2013DMS\u2013MS\u2013MS method. This work revealed current technical limitations of DMS for trace quantification, and practical solutions were implemented. Accurate control of low levels of DMS carrier gas modifier was essential, but required external metering. The linearity of our optimized method was excellent from 0.01 to 6 \u3bcmol L 121. The instrumental LOD was 0.4 pg BMAA injected on-column and the estimated method LOD was 20 ng g 121 dry weight for BMAA in sample matrix. The method was used to analyze cycad plant tissue, a cyanobacterial reference material, and mussel tissues, by use of isotope-dilution quantification with deuterated BMAA. This confirmed the presence of BMAA and several of its isomers in cycad and mussel tissues, including commercially available mussel tissue reference materials certified for other biotoxins.Peer reviewed: YesNRC publication: Ye

Differential Mobility-Mass Spectrometry Double Spike Isotope Dilution Study of Release of β-Methylaminoalanine and Proteinogenic Amino Acids during Biological Sample Hydrolysis

Abstract The non-protein amino acid β-methylamino-L-alanine (BMAA) has been linked to neurodegenerative disease and reported throughout the environment. Proposed mechanisms of bioaccumulation, trophic transfer and chronic toxicity of BMAA rely on the hypothesis of protein misincorporation. Poorly selective methods for BMAA analysis have led to controversy. Here, a recently reported highly selective method for BMAA quantitation using hydrophilic interaction liquid chromatography-differential mobility spectrometry-tandem mass spectrometry (HILIC-DMS-MS/MS) is expanded to include proteinogenic amino acids from hydrolyzed biological samples. For BMAA quantitation, we present a double spiking isotope dilution approach using D3-BMAA and 13C15N2-BMAA. These methods were applied to study release of BMAA during acid hydrolysis under a variety of conditions, revealing that the majority of BMAA can be extracted along with only a small proportion of protein. A time course hydrolysis of BMAA from mussel tissue was carried out to assess the recovery of BMAA during sample preparation. The majority of BMAA measured by typical methods was released before a significant proportion of protein was hydrolyzed. Little change was observed in protein hydrolysis beyond typical hydrolysis times but the concentration of BMAA increased linearly. These findings demonstrate protein misincorporation is not the predominant form of BMAA in cycad and shellfish

Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution.

Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥5%) and nine low-frequency or rare (MAF <5%) coding novel variants. Pathway/gene set enrichment analyses identified lipid particle, adiponectin, abnormal white adipose tissue physiology and bone development and morphology as important contributors to fat distribution, while cross-trait associations highlight cardiometabolic traits. In functional follow-up analyses, specifically in Drosophila RNAi-knockdowns, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). We implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants