Demography and the genetics of age-related diseases.

<p>A schematic representation of the effect of birth cohort and chronological age on the genetic risk of age-related diseases is depicted. The interaction between demographic, environmental, and aging factors allows a genetic risk to emerge (LOCUS green becomes LOCUS X red) only in the presence of a unique combination of chronological age and birth cohort, due to the combined effect of changes in the environmental pressures and the physiopathological remodelling that occurs with age.</p

Genome-Wide Scan Informed by Age-Related Disease Identifies Loci for Exceptional Human Longevity

<div><p>We developed a new statistical framework to find genetic variants associated with extreme longevity. The method, informed GWAS (iGWAS), takes advantage of knowledge from large studies of age-related disease in order to narrow the search for SNPs associated with longevity. To gain support for our approach, we first show there is an overlap between loci involved in disease and loci associated with extreme longevity. These results indicate that several disease variants may be depleted in centenarians versus the general population. Next, we used iGWAS to harness information from 14 meta-analyses of disease and trait GWAS to identify longevity loci in two studies of long-lived humans. In a standard GWAS analysis, only one locus in these studies is significant (<i>APOE/TOMM40</i>) when controlling the false discovery rate (FDR) at 10%. With iGWAS, we identify eight genetic loci to associate significantly with exceptional human longevity at FDR < 10%. We followed up the eight lead SNPs in independent cohorts, and found replication evidence of four loci and suggestive evidence for one more with exceptional longevity. The loci that replicated (FDR < 5%) included <i>APOE/TOMM40</i> (associated with Alzheimer’s disease), <i>CDKN2B/ANRIL</i> (implicated in the regulation of cellular senescence), <i>ABO</i> (tags the O blood group), and <i>SH2B3/ATXN2</i> (a signaling gene that extends lifespan in <i>Drosophila</i> and a gene involved in neurological disease). Our results implicate new loci in longevity and reveal a genetic overlap between longevity and age-related diseases and traits, including coronary artery disease and Alzheimer’s disease. iGWAS provides a new analytical strategy for uncovering SNPs that influence extreme longevity, and can be applied more broadly to boost power in other studies of complex phenotypes.</p></div

Disease GWAS show substantial genetic overlap with longevity.

<p>Shown are results for coronary artery disease and Alzheimer’s disease. The y axis is the observed P values for longevity[<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005728#pgen.1005728.ref003" target="_blank">3</a>], and the x axis is the expected P values under the null hypothesis that the disease is independent of longevity. The cyan, blue and purple lines show the P values for longevity of the top 100, 250, and 500 disease SNPs from independent genetic loci, respectively. Red lines show the background distribution of longevity P values for all independent genetic loci tested in both the longevity and disease GWAS. The grey horizontal line corresponds to the threshold for nominal significance (P< = 0.05) for longevity. Significance of enrichment was determined with the hypergeometric test. (*) P < 0.05, (**) P < 0.005. Q-Q plots for other diseases and traits are shown in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005728#pgen.1005728.s002" target="_blank">S1</a> and <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005728#pgen.1005728.s003" target="_blank">S2</a> Figs.</p

Regional plots for four longevity-associated SNPs.

<p>The y axis shows weighted P values and the x axis indicates position of the SNPs. Color of the SNP indicates linkage to the lead SNP (purple). Green boxes indicate genes harboring missense SNPs in LD with candidate longevity SNPs, and magenta boxes indicate genes whose expression is associated with a candidate longevity SNP (eQTL). A. Data for rs4420638 in APE/TOMM40. B. Data for rs497756 in CDKN2B. C. Data for rs514659 in ABO. D. Data for rs3184504 in SH2B3.</p

Nominal associations with multiple diseases for longevity loci.

<p>Shown are raw P values for each lead longevity SNP in each of the 14 meta-analyses of disease GWA studies that contributed to the cross-disease analysis used by iGWAS. Colors of blue indicate P values in the disease GWAS. The darkest blue corresponds to genome-wide significance. ADIP, adiponectin levels; LOAD, late-onset Alzheimer's disease; AMD, age-related macular degeneration; ART, rheumatoid arthritis; BMD, bone mineral density; BMI, body mass index; DBP, diastolic blood pressure; DIA, type 2 diabetes; CAD, coronary artery disease; INS, fasting insulin levels; CKD, chronic kidney disease; CAN_LUNG, lung cancer; CAN_PANC, pancreatic cancer; TCHO, total cholesterol.</p

Analysis of Population Substructure in Two Sympatric Populations of Gran Chaco, Argentina

<div><p>Sub-population structure and intricate kinship dynamics might introduce biases in molecular anthropology studies and could invalidate the efforts to understand diseases in highly admixed populations. In order to clarify the previously observed distribution pattern and morbidity of Chagas disease in Gran Chaco, Argentina, we studied two populations (Wichí and Criollos) recruited following an innovative bio-cultural model considering their complex cultural interactions. By reconstructing the genetic background and the structure of these two culturally different populations, the pattern of admixture, the correspondence between genealogical and genetic relationships, this integrated perspective had the power to validate data and to link the gap usually relying on a singular discipline. Although Wichí and Criollos share the same area, these sympatric populations are differentiated from the genetic point of view as revealed by Non Recombinant Y Chromosome genotyping resulting in significantly high Fst values and in a lower genetic variability in the Wichí population. Surprisingly, the Amerindian and the European components emerged with comparable amounts (20%) among Criollos and Wichí respectively. The detailed analysis of mitochondrial DNA showed that the two populations have as much as 87% of private haplotypes. Moreover, from the maternal perspective, despite a common Amerindian origin, an Andean and an Amazonian component emerged in Criollos and in Wichí respectively. Our approach allowed us to highlight that quite frequently there is a discrepancy between self-reported and genetic kinship. Indeed, if self-reported identity and kinship are usually utilized in population genetics as a reliable proxy for genetic identity and parental relationship, in our model populations appear to be the result not only and not simply of the genetic background but also of complex cultural determinants. This integrated approach paves the way to a rigorous reconstruction of demographic and cultural history as well as of bioancestry and propensity to diseases of Wichí and Criollos.</p></div

1A. The abundance of α(1,6)-arm monogalactosylated, core-α-1,6-fucosylated diantennary glycan NG1(6)A2F, assessed by peak 3 (P3) levels, in CTR and T2DM patients with and without MS.

<p>The boxplots represent a comparison of peak 3 levels in males in six classes of subjects: CTR without MS, CTR with MS, T2DM- without MS, T2DM- with MS, T2DM+ without MS, T2DM+ with MS. <b>1B.</b> The abundance of α(1,6)-arm monogalactosylated, core-α-1,6-fucosylated diantennary glycan NG1(6)A2F, assessed by peak 3 (P3) levels, in CTR and T2DM patients with and without MS. The boxplots represent a comparison of peak 3 levels in females in six classes of subjects: CTR without MS, CTR with MS, T2DM- without MS, T2DM- with MS, T2DM+ without MS, T2DM+ with MS.</p

Comparison of the content and size of different standard file formats for the storage of genomic data.

<p>Comparison of the content and size of different standard file formats for the storage of genomic data.</p

The Use of Non-Variant Sites to Improve the Clinical Assessment of Whole-Genome Sequence Data

<div><p>Genetic testing, which is now a routine part of clinical practice and disease management protocols, is often based on the assessment of small panels of variants or genes. On the other hand, continuous improvements in the speed and per-base costs of sequencing have now made whole exome sequencing (WES) and whole genome sequencing (WGS) viable strategies for targeted or complete genetic analysis, respectively. Standard WGS/WES data analytical workflows generally rely on calling of sequence variants respect to the reference genome sequence. However, the reference genome sequence contains a large number of sites represented by rare alleles, by known pathogenic alleles and by alleles strongly associated to disease by GWAS. It’s thus critical, for clinical applications of WGS and WES, to interpret whether non-variant sites are homozygous for the reference allele or if the corresponding genotype cannot be reliably called. Here we show that an alternative analytical approach based on the analysis of both variant and non-variant sites from WGS data allows to genotype more than 92% of sites corresponding to known SNPs compared to 6% genotyped by standard variant analysis. These include homozygous reference sites of clinical interest, thus leading to a broad and comprehensive characterization of variation necessary to an accurate evaluation of disease risk. Altogether, our findings indicate that characterization of both variant and non-variant clinically informative sites in the genome is necessary to allow an accurate clinical assessment of a personal genome. Finally, we propose a highly efficient extended VCF (eVCF) file format which allows to store genotype calls for sites of clinical interest while remaining compatible with current variant interpretation software.</p></div

Compatibility of the eVCF file format with different variation analysis suites.

<p>Compatibility of the eVCF file format with different variation analysis suites.</p