The CEPH aging cohort and biobank: a valuable collection of biological samples from exceptionally long-lived French individuals and their offspring for longevity studies.

The increasing aging of the human population is currently and for the coming decades a major public health issue in many countries, requiring the implementation of global public health policies promoting healthy and successful aging. Individuals are not equal in the face of aging and some can present exceptional healthspan and/or lifespan, which are notably influenced by both genetic and environmental factors. Research and studies on human aging, healthy aging and longevity should rely in particular on cohorts of long-lived individuals, also including biological samples allowing studies on the biology of aging and longevity. In this manuscript, we provide for the first time a complete description of the CEPH (Centre d'Etude du Polymophisme Humain) Aging cohort, an exceptional cohort recruited during the 90s to 2000s, including more than 1700 French long-lived individuals (≥ 90 years old) born between 1875 and 1916 as well as for some of them their siblings and offspring. Among the participants, 1265 were centenarians, including 255 semi-supercentenarians ([105-110] years old) and 25 supercentenarians (≥ 110 years old). The available anthropometric, epidemiologic and clinical data for the cohort participants are described and especially the collection of blood-derived biological samples associated with the cohort which includes DNA, cryopreserved cells and cell lines, plasma, and serum. This biological collection from the first cohort of centenarians in the world is an inestimable resource for ongoing and future molecular, cellular, and functional studies aimed at deciphering the mechanisms of human (successful) aging and longevity.

Centenarians consistently present a younger epigenetic age than their chronological age with four epigenetic clocks based on a small number of CpG sites.

Aging is a progressive time-dependent biological process affecting differentially individuals, who can sometimes present exceptional longevity. Epigenetic alterations are one of the hallmarks of aging, which comprise the epigenetic drift and clock at DNA methylation level. In the present study, we estimated the DNA methylation-based age (DNAmage) using four epigenetic clocks based on a small number of CpGs in French centenarians and semi-supercentenarians (CSSC, n=214) as well as nonagenarians' and centenarians' offspring (NCO, n=143) compared to individuals from the French general population (CG, n=149). DNA methylation analysis of the nine CpGs included in the epigenetic clocks showed high correlation with chronological age (-0.66>R>0.54) and also the presence of an epigenetic drift for four CpGs that was only visible in CSSC. DNAmage analysis showed that CSSC and to a lesser extend NCO present a younger DNAmage than their chronological age (15-28.5 years for CSSC, 4.4-11.5 years for NCO and 4.2-8.2 years for CG), which were strongly significant in CSSC compared to CG (p-values<2.2e-16). These differences suggest that epigenetic aging and potentially biological aging are slowed in exceptionally long-lived individuals and that epigenetic clocks based on a small number of CpGs are sufficient to reveal alterations of the global epigenetic clock.

A high-throughput real-time PCR tissue-of-origin test to distinguish blood from lymphoblastoid cell line DNA for (epi)genomic studies.

Lymphoblastoid cell lines (LCLs) derive from blood infected in vitro by Epstein-Barr virus and were used in several genetic, transcriptomic and epigenomic studies. Although few changes were shown between LCL and blood genotypes (SNPs) validating their use in genetics, more were highlighted for other genomic features and/or in their transcriptome and epigenome. This could render them less appropriate for these studies, notably when blood DNA could still be available. Here we developed a simple, high-throughput and cost-effective real-time PCR approach allowing to distinguish blood from LCL DNA samples based on the presence of EBV relative load and rearranged T-cell receptors γ and ß. Our approach was able to achieve 98.5% sensitivity and 100% specificity on DNA of known origin (458 blood and 316 LCL DNA). It was further applied to 1957 DNA samples from the CEPH Aging cohort comprising DNA of uncertain origin, identifying 784 blood and 1016 LCL DNA. A subset of these DNA was further analyzed with an epigenetic clock indicating that DNA extracted from blood should be preferred to LCL for DNA methylation-based age prediction analysis. Our approach could thereby be a powerful tool to ascertain the origin of DNA in old collections prior to (epi)genomic studies.

Improvements and inter-laboratory implementation and optimization of blood-based single-locus age prediction models using DNA methylation of the ELOVL2 promoter.

Several blood-based age prediction models have been developed using less than a dozen to more than a hundred DNA methylation biomarkers. Only one model (Z-P1) based on pyrosequencing has been developed using DNA methylation of a single locus located in the ELOVL2 promoter, which is considered as one of the best age-prediction biomarker. Although multi-locus models generally present better performances compared to the single-locus model, they require more DNA and present more inter-laboratory variations impacting the predictions. Here we developed 17,018 single-locus age prediction models based on DNA methylation of the ELOVL2 promoter from pooled data of four different studies (training set of 1,028 individuals aged from 0 and 91 years) using six different statistical approaches and testing every combination of the 7 CpGs, aiming to improve the prediction performances and reduce the effects of inter-laboratory variations. Compared to Z-P1 model, three statistical models with the optimal combinations of CpGs presented improved performances (MAD of 4.41-4.77 in the testing set of 385 individuals) and no age-dependent bias. In an independent testing set of 100 individuals (19-65 years), we showed that the prediction accuracy could be further improved by using different CpG combinations and increasing the number of technical replicates (MAD of 4.17).

Tumor DNA hypomethylation of LINE-1 is associated with low tumor grade of breast cancer in Tunisian patients.

DNA hypomethylation of long interspersed repetitive DNA retrotransposon (LINE-1) and Alu repeats elements of short interspersed elements family (SINEs) is an early event in carcinogenesis that causes transcriptional activation and leads to chromosomal instability. In the current study, DNA methylation levels of LINE-1 and Alu repeats were analyzed in tumoral tissues of invasive breast cancer in a Tunisian cohort and its association with the clinicopathological features of patients was defined. DNA methylation of LINE-1 and Alu repeats were analyzed using pyrosequencing in 61 invasive breast cancers. Median values observed for DNA methylation of LINE-1 and Alu repeats were considered as the cut-off (59.81 and 18.49%, respectively). The results of the current study demonstrated a positive correlation between DNA methylation levels of LINE-1 and Alu repeats (rho=0.284; P<0.03). DNA hypomethylation of LINE-1 was also indicated to be associated with low grade (P=0.023). To the best of our knowledge, the current study is the first study regarding DNA methylation of LINE-1 and Alu repeats element in breast cancer of the Tunisian population. The results of the current study suggest that, since hypomethylation of LINE-1 is associated with low grade, it could be used as a biomarker for prognosis for patients with breast cancer.

Estimating the age of p.(Phe508del) with family studies of geographically distinct European populations and the early spread of cystic fibrosis.

The high incidence of cystic fibrosis (CF) is due to the frequency of the c.1521_1523delCTT variant in the cystic fibrosis transmembrane conductance regulator (CFTR), but its age and origin are uncertain. This gap limits attempts to shed light on the presumed heterozygote selective advantage that accounts for the variant's high prevalence among Caucasian Europeans and Europe-derived populations. In addition, explaining the nature of heterozygosity to screened individuals with one c.1521_1523delCTT variant is challenging when families raise questions about these issues. To address this gap, we obtained DNA samples from 190 patients bearing c.1521_1523delCTT and their parents residing in geographically distinct European populations plus a Germany-derived population in the USA. We identified microsatellites spanning CFTR and reconstructed haplotypes at 10 loci to estimate the time/age of the most recent common ancestor (tMRCA) with the Estiage program. We found that the age estimates differ between northwestern populations, where the mean tMRCA values vary between 4600 and 4725 years, and the southeastern populations where c.1521_1523delCTT seems to have been introduced only about 1000 years ago. The tMRCA values of Central Europeans were intermediate. Thus, our data resolve a controversy by establishing an early Bronze Age origin of the c.1521_1523delCTT allele and demonstrating its likely spread from northwest to southeast during ancient migrations. Moreover, taking the archeological record into account, our results introduce a novel concept by suggesting that Bell Beaker folk were the probable migrating population responsible for the early dissemination of c.1521_1523delCTT in prehistoric Europe.

Major improvement in the detection of microsatellite instability in colorectal cancer using HSP110 T17 E-ice-COLD-PCR.

Every colorectal cancer (CRC) patient should be tested for microsatellite instability (MSI) to screen for Lynch syndrome. Evaluation of MSI status involves screening tumor DNA for the presence of somatic deletions in DNA repeats using PCR followed by fragment analysis. While this method may lack sensitivity due to the presence of a high level of germline DNA, which frequently contaminates the core of primary colon tumors, no other method developed to date is capable of modifying the standard PCR protocol to achieve improvement of MSI detection. Here, we describe a new approach developed for the ultra-sensitive detection of MSI in CRC based on E-ice-COLD-PCR, using HSP110 T17, a mononucleotide DNA repeat previously proposed as an optimal marker to detect MSI in tumor DNA, and an oligo(dT)16 LNA blocker probe complementary to wild-type genotypes. The HT17 E-ice-COLD-PCR assay improved MSI detection by 20-200-fold compared with standard PCR using HT17 alone. It presents an analytical sensitivity of 0.1%-0.05% of mutant alleles in wild-type background, thus greatly improving MSI detection in CRC samples highly contaminated with normal DNA. HT17 E-ice-COLD-PCR is a rapid, cost-effective, easy-to-implement, and highly sensitive method, which could significantly improve the detection of MSI in routine clinical testing.

Assessment of the prognostic role of a 94-single nucleotide polymorphisms risk score in early breast cancer in the SIGNAL/PHARE prospective cohort: no correlation with clinico-pathological characteristics and outcomes.

BACKGROUND: Genome-wide association studies (GWAS) have to date identified 94 genetic variants (single nucleotide polymorphisms (SNPs)) associated with risk of developing breast cancer. A score based on the combined effect of the 94 risk alleles can be calculated to measure the global risk of breast cancer. We aimed to test the hypothesis that the 94-SNP-based risk score is associated with clinico-pathological characteristics, breast cancer subtypes and outcomes in early breast cancer. METHODS: A 94-SNP risk score was calculated in 8703 patients in the PHARE and SIGNAL prospective case cohorts. This score is the total number of inherited risk alleles based on 94 selected SNPs. Clinical data and outcomes were prospectively registered. Genotyping was obtained from a GWAS. RESULTS: The median 94-SNP risk score in 8703 patients with early breast cancer was 77.5 (range: 58.1-97.6). The risk score was not associated with usual prognostic and predictive factors (age; tumor, node, metastasis (TNM) status; Scarff-Bloom-Richardson grade; inflammatory features; estrogen receptor status; progesterone receptor status; human epidermal growth factor receptor 2 (HER2) status) and did not correlate with breast cancer subtypes. The 94-SNP risk score did not predict outcomes represented by overall survival or disease-free survival. CONCLUSIONS: In a prospective case cohort of 8703 patients, a risk score based on 94 SNPs was not associated with breast cancer characteristics, cancer subtypes, or patients' outcomes. If we hypothesize that prognosis and subtypes of breast cancer are determined by constitutional genetic factors, our results suggest that a score based on breast cancer risk-associated SNPs is not associated with prognosis. TRIAL REGISTRATION: PHARE cohort: NCT00381901 , Sept. 26, 2006 - SIGNAL cohort: INCa RECF1098, Jan. 28, 2009.

Constitutional variants are not associated with HER2-positive breast cancer: results from the SIGNAL/PHARE clinical cohort.

Human epidermal growth factor receptor 2-positive breast cancer is a subtype of interest regarding its outcome and the impressive impact of human epidermal growth factor receptor 2 targeted therapy. Constitutional variants may be involved in the aetiology of human epidermal growth factor receptor 2-positive breast cancer, and we propose a case-case study to test the hypothesis that single nucleotide polymorphisms may be associated with human epidermal growth factor receptor 2 status. A Genome-Wide Association Study was used in a cohort of 9836 patients from the SIGNAL/PHARE study (NCT00381901-RECF1098). The main goal was to identify variants specifically related to human epidermal growth factor receptor 2-positive breast cancer. A two-staged genotyping strategy was carried out to cover as large a proportion of the genome as possible. All subjects were genotyped using the Illumina HumanCore Exome chip set. Principal Components Analysis and k-means were then used to characterize the ancestry of the participants. A random sample of subjects from the main "European" cluster was genotyped with the Omni5 chip set. These data were then used to impute missing genotypes from the remaining subjects genotyped only using the HumanCore Exome array. From the 9836 patients, a total of 8703 cases including 3230 patients with human epidermal growth factor receptor 2-positive breast cancer were analyzed. Despite having 80% power to detect an odds ratio of 1.23 in this population, no variant achieved genome-wide significance for association with the occurrence of human epidermal growth factor receptor 2-positive breast cancer vs. any other subtype of breast tumour. Our study was unable to identify constitutional polymorphisms that are strongly associated with human epidermal growth factor receptor 2-positive status among breast cancer patients.

GWAS in the SIGNAL/PHARE clinical cohort restricts the association between the FGFR2 locus and estrogen receptor status to HER2-negative breast cancer patients.

Genetic polymorphisms are associated with breast cancer risk. Clinical and epidemiological observations suggest that clinical characteristics of breast cancer, such as estrogen receptor or HER2 status, are also influenced by hereditary factors. To identify genetic variants associated with pathological characteristics of breast cancer patients, a Genome Wide Association Study was performed in a cohort of 9365 women from the French nationwide SIGNAL/PHARE studies (NCT00381901/RECF1098). Strong association between the FGFR2 locus and ER status of breast cancer patients was observed (ER-positive n=6211, ER-negative n=2516; rs3135718 OR=1.34 p=5.46×10-12). This association was limited to patients with HER2-negative tumors (ER-positive n=4267, ER-negative n=1185; rs3135724 OR=1.85 p=1.16×10-11). The FGFR2 locus is known to be associated with breast cancer risk. This study provides sound evidence for an association between variants in the FGFR2 locus and ER status among breast cancer patients, particularly among patients with HER2-negative disease. This refinement of the association between FGFR2 variants and ER-status to HER2-negative disease provides novel insight to potential biological and clinical influence of genetic polymorphisms on breast tumors.

Loss of VPS13C Function in Autosomal-Recessive Parkinsonism Causes Mitochondrial Dysfunction and Increases PINK1/Parkin-Dependent Mitophagy.

Autosomal-recessive early-onset parkinsonism is clinically and genetically heterogeneous. The genetic causes of approximately 50% of autosomal-recessive early-onset forms of Parkinson disease (PD) remain to be elucidated. Homozygozity mapping and exome sequencing in 62 isolated individuals with early-onset parkinsonism and confirmed consanguinity followed by data mining in the exomes of 1,348 PD-affected individuals identified, in three isolated subjects, homozygous or compound heterozygous truncating mutations in vacuolar protein sorting 13C (VPS13C). VPS13C mutations are associated with a distinct form of early-onset parkinsonism characterized by rapid and severe disease progression and early cognitive decline; the pathological features were striking and reminiscent of diffuse Lewy body disease. In cell models, VPS13C partly localized to the outer membrane of mitochondria. Silencing of VPS13C was associated with lower mitochondrial membrane potential, mitochondrial fragmentation, increased respiration rates, exacerbated PINK1/Parkin-dependent mitophagy, and transcriptional upregulation of PARK2 in response to mitochondrial damage. This work suggests that loss of function of VPS13C is a cause of autosomal-recessive early-onset parkinsonism with a distinctive phenotype of rapid and severe progression.

High level of inbreeding in final phase of 1000 Genomes Project.

The 1000 Genomes Project provides a unique source of whole genome sequencing data for studies of human population genetics and human diseases. The last release of this project includes more than 2,500 sequenced individuals from 26 populations. Although relationships among individuals have been investigated in some of the populations, inbreeding has never been studied. In this article, we estimated the genomic inbreeding coefficient of each individual and found an unexpected high level of inbreeding in 1000 Genomes data: nearly a quarter of the individuals were inbred and around 4% of them had inbreeding coefficients similar or greater than the ones expected for first-cousin offspring. Inbred individuals were found in each of the 26 populations, with some populations showing proportions of inbred individuals above 50%. We also detected 227 previously unreported pairs of close relatives (up to and including first-cousins). Thus, we propose subsets of unrelated and outbred individuals, for use by the scientific community. In addition, because admixed populations are present in the 1000 Genomes Project, we performed simulations to study the robustness of inbreeding coefficient estimates in the presence of admixture. We found that our multi-point approach (FSuite) was quite robust to admixture, unlike single-point methods (PLINK).

A new F-box protein 7 gene mutation causing typical Parkinson's disease.

BACKGROUND: Recessive mutations in the F-box protein 7 gene (FBXO7; PARK15) have been identified as a cause of the parkinsonian-pyramidal syndrome. Here, we report clinical and genetic findings in a Turkish family with novel FBXO7 mutations. METHODS: Whole exome and targeted Sanger sequencing were performed for genetic analysis in a family with two members affected by Parkinson's disease (PD). All family members underwent detailed clinical, mental, and neurological examination. RESULTS: The new p.L34R (c.101 T>G) FBXO7 mutation was detected in a homozygous state in two Turkish sibs with typical levodopa-responsive PD. CONCLUSION: This is the first time a FBXO7 mutation has been identified that causes a phenotype compatible with typical idiopathic PD and presents with some of its common nonmotor features, such as rapid eye movement sleep behavior disorder, depression, and anxiety.

Genome-wide inbreeding estimation within Lebanese communities using SNP arrays.

Consanguineous marriages have been widely practiced in several global communities with varying rates depending on religion, culture, and geography. In consanguineous marriages, parents pass to their children autozygous segments known as homozygous by descent segments. In this study, single-nucleotide polymorphisms were analyzed in 165 unrelated Lebanese people from Greek Orthodox, Maronite, Shiite and Sunni communities. Runs of homozygosity, total inbreeding levels, remote consanguinity, and population admixture and structure were estimated. The inbreeding coefficient value was estimated to be 1.61% in offspring of unrelated parents over three generations and 8.33% in offspring of first cousins. From these values, remote consanguinity values, resulting from genetic drift or recurrent consanguineous unions, were estimated in offspring of unrelated and first-cousin parents to be 0.61 and 1.2%, respectively. This remote consanguinity value suggests that for any unrelated marriages in Lebanon, the mates could be related as third cousins or as second cousins once removed. Under the assumption that 25% of marriages occur between first cousins, the mean inbreeding value of 2.3% may explain the increased incidence of recessive disease in offspring. Our analysis reveals a common ancestral population in the four Lebanese communities we studied.

Inbreeding coefficient estimation with dense SNP data: comparison of strategies and application to HapMap III.

BACKGROUND/AIMS: If the parents of an individual are related, it is possible for the individual to have received at 1 locus 2 identical-by-descent alleles that are copies of a single allele carried by the parents' common ancestor. The inbreeding coefficient measures the probability of this event and increases with increasing relatedness between the parents. It is traditionally computed from the observed inbreeding loops in the genealogies and its accuracy thus depends on the depth and reliability of the genealogies. With the availability of genome-wide genetic data, it has become possible to compute a genome-based inbreeding coefficient f, and different methods have been developed to estimate f and identify inbred individuals in a sample from the observed patterns of homozygosity at markers. METHODS: For this paper, we performed simulations with known genealogies using different SNP panels with different levels of linkage disequilibrium (LD) to compare several estimators of f, including single-point estimates, methods based on the length of runs of homozygosity (ROHs) and different methods that use hidden Markov models (HMMs). We also compared the performances of some of these estimators to identify inbred individuals in a sample using either HMM likelihood ratio tests or an adapted version of the ERSA software. RESULTS: Single-point methods were found to have higher standard deviations than other methods. ROHs gave the best estimates provided the correct length threshold is known. HMMs on sparse data gave equivalent or better results than HMMs modeling LD. Provided LD is correctly accounted for, the inbreeding estimates were very similar using the different SNP panels. The HMM likelihood ratio tests were found to perform better at detecting inbred individuals in a sample than the adapted ERSA. All methods accurately detected inbreeding up to second-cousin offspring. We applied the best method on release 3 of the HapMap phase III project, found up to 4% of inbred individuals, and created HAP1067, an unrelated and outbred dataset of this release. CONCLUSIONS: We recommend using HMMs on multiple sparse maps to estimate and detect inbreeding in large samples. If the sample of individuals is too small to estimate allele frequencies, we advise to estimate them on reference panels or to use 1,500-kb ROHs. Finally, we suggest to investigators using HapMap to be careful with inbred individuals, especially in the GIH (Gujarati Indians from Houston in Texas) population.

FSuite: exploiting inbreeding in dense SNP chip and exome data.

UNLABELLED: FSuite is a user-friendly pipeline developed for exploiting inbreeding information derived from human genomic data. It can make use of single nucleotide polymorphism chip or exome data. Compared with other software, the advantage of FSuite is that it provides a complete suite of scripts to describe and use the inbreeding information. It includes a module to detect inbred individuals and estimate their inbreeding coefficient, a module to describe the proportion of different mating types in the population and the individual probability to be offspring of different mating types that can be useful for population genetic studies. It also allows the identification of shared regions of homozygosity between affected individuals (homozygosity mapping) that can be used to identify rare recessive mutations involved in monogenic or multifactorial diseases. AVAILABILITY AND IMPLEMENTATION: FSuite is developed in Perl and uses R functions to generate graphical outputs. This pipeline is freely available under GNU GPL license at: http://genestat.cephb.fr/software/index.php/FSuite.

Comparative power of family-based association strategies to detect disease-causing variants under two-locus models.

Not accounting for interaction in association analyses may reduce the power to detect the variants involved. We investigate the powers of different designs to detect under two-locus models the effect of disease-causing variants among several hundreds of markers using family-based association tests by simulation. This setting reflects realistic situations of exploration of linkage regions or of biological pathways. We define four strategies: (S1) single-marker analysis of all Single Nucleotide Polymorphisms (SNPs), (S2) two-marker analysis of all possible SNPs pairs, (S3) lax preliminary selection of SNPs followed by a two-marker analysis of all selected SNP pairs, (S4) stringent preliminary selection of SNPs, each being later paired with all the SNPs for two-marker analysis. Strategy S2 is never the best design, except when there is an inversion of the gene effect (flip-flop model). Testing individual SNPs (S1) is the most efficient when the two genes act multiplicatively. Designs S3 and S4 are the most powerful for nonmultiplicative models. Their respective powers depend on the level of symmetry of the model. Because the true genetic model is unknown, we cannot conclude that one design outperforms another. The optimal approach would be the two-step strategy (S3 or S4) as it is often the most powerful, or the second best.