Presymptomatic risk assessment for chronic non-communicable diseases

The prevalence of common chronic non-communicable diseases (CNCDs) far overshadows the prevalence of both monogenic and infectious diseases combined. All CNCDs, also called complex genetic diseases, have a heritable genetic component that can be used for pre-symptomatic risk assessment. Common single nucleotide polymorphisms (SNPs) that tag risk haplotypes across the genome currently account for a non-trivial portion of the germ-line genetic risk and we will likely continue to identify the remaining missing heritability in the form of rare variants, copy number variants and epigenetic modifications. Here, we describe a novel measure for calculating the lifetime risk of a disease, called the genetic composite index (GCI), and demonstrate its predictive value as a clinical classifier. The GCI only considers summary statistics of the effects of genetic variation and hence does not require the results of large-scale studies simultaneously assessing multiple risk factors. Combining GCI scores with environmental risk information provides an additional tool for clinical decision-making. The GCI can be populated with heritable risk information of any type, and thus represents a framework for CNCD pre-symptomatic risk assessment that can be populated as additional risk information is identified through next-generation technologies.Comment: Plos ONE paper. Previous version was withdrawn to be updated by the journal's pdf versio

C9orf72 ALS/FTD dipeptide repeat protein levels are reduced by small molecules that inhibit PKA or enhance protein degradation

Intronic GGGGCC (G4C2) hexanucleotide repeat expansion within the human C9orf72 gene represents the most common cause of familial forms of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) (C9ALS/FTD). Repeat-associated non-AUG (RAN) translation of repeat-containing C9orf72 RNA results in the production of neurotoxic dipeptide-repeat proteins (DPRs). Here, we developed a high-throughput drug screen for the identification of positive and negative modulators of DPR levels. We found that HSP90 inhibitor geldanamycin and aldosterone antagonist spironolactone reduced DPR levels by promoting protein degradation via the proteasome and autophagy pathways respectively. Surprisingly, cAMP-elevating compounds boosting protein kinase A (PKA) activity increased DPR levels. Inhibition of PKA activity, by both pharmacological and genetic approaches, reduced DPR levels in cells and rescued pathological phenotypes in a Drosophila model of C9ALS/FTD. Moreover, knockdown of PKA-catalytic subunits correlated with reduced translation efficiency of DPRs, while the PKA inhibitor H89 reduced endogenous DPR levels in C9ALS/FTD patient-derived iPSC motor neurons. Together, our results suggest new and druggable pathways modulating DPR levels in C9ALS/FTD

The use of measured genotype information in the analysis of quantitative phenotypes in man.

We have begun a measured genotype approach to the genetic analysis of lipid and lipoprotein variability. This approach enables one to simultaneously estimate the frequencies and effects of alleles at specific loci along with the residual polygenetic variance component. In this study we consider the contribution of three common alleles at the locus coding for apolipoprotein E to interindividual variation of total cholesterol, betalipoprotein, and triglyceride levels. A sample of 102 nuclear families consisting of 434 individuals was studied. The frequencies of the ε2, ε3, and ε4 alleles in this sample are 0·137,0·740, and 0·123, respectively. In separate analyses of cholesterol and betalipoprotein levels, a complete model that includes the effects of the six apo E genotypes, unmeasured polygenes, and individual specific environmental effects fits these data significantly better than a reduced model that does not include the effects of the apo E polymorphism or a reduced model that does not include the effects of polygenes. On the average the ε2 allele lowers total cholesterol and betalipoprotein levels by 0·425 mmol/l and 0·811 units, respectively. The ε4 allele is associated with an average increase of these phenotypes by 0·255 mmol/l and 0·628 units, respectively. Simultaneous estimates of the interindividual variability of total cholesterol levels attributable to the apo E polymorphism and to residual polygenic effects are 8% and 56%, respectively. For betalipoprotein levels, we simultaneously estimate these values to be 7% and 42%, respectively. A reduced model including the effects of polygenes but not the effects of the apo E polymorphism fitted the triglyceride data as well as the complete model. The estimate of the fraction of interindividual variability associated with polygenetic effects was 26.5%. We review our present understanding of the genetic architecture underlying variability of cholesterol levels in the population at large and infer that the majority of the genetic variability may be accounted for by polymorphic gene loci with moderate effects on cholesterol levels.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65212/1/j.1469-1809.1987.tb00874.x.pd

Different strategies for recovering metals from CARON process residue

http://dx.doi.org/10.1016/j.jhazmat.2011.03.048The capacity of Acidithiobacillus thiooxidans DMS 11478 to recover the heavy metals contained in the residue obtained from the CARON process has been evaluated. Different bioreactor configurations were studied: a two-stage batch system and two semi-continuous systems (stirred-tank reactor leaching and column leaching). In the two-stage system, 46.8% Co, 36.0% Mg, 26.3% Mn and 22.3% Ni were solubilised after 6 h of contact between the residue and the bacteria-free bioacid. The results obtained with the stirred-tank reactor and the column were similar: 50% of the Mg and Co and 40% of the Mn and Ni were solubilised after thirty one days. The operation in the column reactor allowed the solid–liquid ratio to be increased and the pH to be kept at low values (<1.0). Recirculation of the leachate in the column had a positive effect on metal removal; at sixty five days (optimum time) the solubilisation levels were as follows: 86% Co, 83% Mg, 72% Mn and Ni, 62% Fe and 23% Cr. The results corroborate the feasibility of the systems studied for the leaching of metals from CARON process residue and these methodologies can be considered viable for the recovery of valuable metals

AKT signalling selectively regulates PINK1 mitophagy in SHSY5Y cells and human iPSC-derived neurons

The discovery of mutations within genes associated with autosomal recessive Parkinson's disease allowed for the identification of PINK1/Parkin regulated mitophagy as an important pathway for the removal of damaged mitochondria. While recent studies suggest that AKT-dependent signalling regulates Parkin recruitment to depolarised mitochondria, little is known as to whether this can also regulate PINK1 mitochondrial accumulation and downstream mitophagy. Here, we demonstrate that inhibition of AKT signalling decreases endogenous PINK1 accumulation in response to mitochondria depolarisation, subsequent Parkin recruitment, phosphorylation of ubiquitin, and ultimately mitophagy. Conversely, we show that upon stimulation of AKT signalling via insulin, the mitophagy pathway is increased in SHSY5Y cells. These data suggest that AKT signalling is an upstream regulator of PINK1 accumulation on damaged mitochondria. Importantly, we show that the AKT pathway also regulates endogenous PINK1-dependent mitophagy in human iPSC-derived neurons

Quantitative genetics theory for genomic selection and efficiency of genotypic value prediction in open-pollinated populations

ABSTRACT: Quantitative genetics theory for genomic selection has mainly focused on additive effects. This study presents quantitative genetics theory applied to genomic selection aiming to prove that prediction of genotypic value based on thousands of single nucleotide polymorphisms (SNPs) depends on linkage disequilibrium (LD) between markers and QTLs, assuming dominance and epistasis. Based on simulated data, we provided information on dominance and genotypic value prediction accuracy, assuming mass selection in an open-pollinated population, all quantitative trait loci (QTLs) of lower effect, and reduced sample size. We show that the predictor of dominance value is proportional to the square of the LD value and to the dominance deviation for each QTL that is in LD with each marker. The weighted (by the SNP frequencies) dominance value predictor has greater accuracy than the unweighted predictor. The linear × linear, linear × quadratic, quadratic × linear, and quadratic × quadratic SNP effects are proportional to the corresponding linear combinations of epistatic effects for QTLs and the LD values. LD between two markers with a common QTL causes a bias in the prediction of epistatic values. Compared to phenotypic selection, the efficiency of genomic selection for genotypic value prediction increases as trait heritability decreases. The degree of dominance did not affect the genotypic value prediction accuracy and the approach to maximum accuracy is asymptotic with increases in SNP density. The decrease in the sample size from 500 to 200 did not markedly reduce the genotypic value prediction accuracy

QTL mapping in autotetraploids using SNP dosage information

Dense linkage maps derived by analysing SNP dosage in autotetraploids provide detailed information about the location of, and genetic model at, quantitative trait loci. Recent developments in sequencing and genotyping technologies enable researchers to generate high-density single nucleotide polymorphism (SNP) genotype data for mapping studies. For polyploid species, the SNP genotypes are informative about allele dosage, and Hackett et al. (PLoS ONE 8:e63939, 2013) presented theory about how dosage information can be used in linkage map construction and quantitative trait locus (QTL) mapping for an F1 population in an autotetraploid species. Here, QTL mapping using dosage information is explored for simulated phenotypic traits of moderate heritability and possibly non-additive effects. Different mapping strategies are compared, looking at additive and more complicated models, and model fitting as a single step or by iteratively re-weighted modelling. We recommend fitting an additive model without iterative re-weighting, and then exploring non-additive models for the genotype means estimated at the most likely position. We apply this strategy to re-analyse traits of high heritability from a potato population of 190 F1 individuals: flower colour, maturity, height and resistance to late blight (Phytophthora infestans (Mont.) de Bary) and potato cyst nematode (Globodera pallida), using a map of 3839 SNPs. The approximate confidence intervals for QTL locations have been improved by the detailed linkage map, and more information about the genetic model at each QTL has been revealed. For several of the reported QTLs, candidate SNPs can be identified, and used to propose candidate trait genes. We conclude that the high marker density is informative about the genetic model at loci of large effects, but that larger populations are needed to detect smaller QTLs

Coming to terms with heritability

The complex mechanisms of heredity are little appreciated by non-specialists, in some measure, because of misunderstandings that are perpetuated when words used for technical terms have other, more widely understood, folk meanings. When a word has both technical and folk meanings, it is the responsibility of the specialist to avoid promoting confusion by either using extremely cautious and precise language when using the term or, in cases when confusion is inevitable, abandoning the term in favor of one without a widely understood folk meaning. The study of heredity is beset by such confusion, and the term heritability appears to be at the heart of some of the confusion. In this article, I discuss both the technical and folk meanings of heritability and examine the bridge between them. By continuing to use the term heritability, we risk promulgating serious misunderstanding about the workings of heredity, therefore I suggest selectability as an alternative term to avoid such pitfalls.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42804/1/10709_2005_Article_BF02259512.pd